迷走中

ズルズルと何度も繰り返して色々試すけど納得出来るモデルが出ない😞

パラメータ / 指標	条件 1	条件 2	条件 3	条件 4	条件 5	条件 6	条件 7
NumberOfLeaves	79	63	63	63	63	63	63
NumberOfIterations	5,000	3,000	3,000	3,000	3,000	3,000	3,000
LearningRate	0.010	0.010	0.010	0.010	0.010	0.010	0.010
MaximumBin	127	63	63	63	63	63	63
MinimumExample	20	20	20	30	40	50	60
SubsampleFraction	0.050	0.050	0.025	0.050	0.050	0.050	0.050
FeatureFraction	0.800	0.800	0.980	0.800	0.800	0.800	0.800
L2Regularization	0.500	0.500	0.500	0.500	0.500	0.500	0.500
R² （決定係数）	0.2263	0.2334	0.2323	0.2340	0.2340	0.2339	0.2334

まあ、葉の最小は30か40みたいなので30に絞って10回試す。でも、これってAIに毎回質問したりしてるけど、AIも所詮ネット上の情報なんかを元にしてるだけで、実際に全てのパターンを試してる訳じゃないので途方もないパターンの中から最適な設定を探すのは地道なパターン潰ししかない気はしてるんだよね。いや、まあ、それが面倒だからAutoMLが割る訳なんだが(笑)

もしかしたら、またAutoMLで24時間とか回してそのパラメーターを真似するのが最短なのかもしれないけど^^; 新馬戦用走破タイム学習だと葉の数が滅茶苦茶多かったんだよね。

30を10回やったが0.2330～0.2337しか出なかったorz なので40を10回スタートした。まあ、以前は40回とかやってた時だいたい20回程度で良いのが出た事もあったし、これ本当に運任せだから辛い😩なんだろなぁ、0.2334～0.2339しか出ない。でまあ、50を10回やったんだが、ここで、0.2332～0.2341でした😝

2,610R	1点	芝(1,278R)	ダート(1,243R)	障害(89R)	8頭以下(157R)	9～12頭(665R)	13頭以上(1,788R)	多点
単勝	23.91% (78.26%)	23.94% (82.92%)	24.22% (74.10%)	19.10% (69.44%)	33.76% (71.53%)	25.11% (68.42%)	22.60% (82.51%)	53.45% (76.84%)
複勝	54.87% (80.56%)	53.13% (79.22%)	56.40% (81.63%)	58.43% (84.72%)	63.06% (83.50%)	59.10% (80.17%)	52.57% (80.44%)	88.12% (80.68%)
枠連	13.03% (71.94%)	11.95% (68.62%)	13.89% (74.42%)	15.19% (80.51%)	-- (--)	13.98% (70.39%)	11.91% (68.29%)	28.66% (72.86%)
馬連	9.66% (66.23%)	9.15% (65.15%)	10.06% (66.99%)	11.24% (71.24%)	20.38% (97.20%)	11.58% (70.17%)	8.00% (62.05%)	22.76% (69.48%)
ワイド	23.68% (76.26%)	22.38% (71.77%)	25.26% (82.08%)	20.22% (59.44%)	37.58% (74.78%)	27.37% (77.19%)	21.09% (76.04%)	45.63% (76.79%)
馬単	5.52% (70.54%)	5.16% (73.52%)	5.87% (67.51%)	5.62% (70.00%)	12.74% (88.85%)	6.77% (71.50%)	4.42% (68.57%)	22.76% (69.10%)
三連複	6.32% (74.61%)	6.26% (70.16%)	6.44% (77.38%)	5.62% (99.78%)	13.38% (95.22%)	6.77% (76.32%)	5.54% (72.16%)	16.05% (71.69%)
三連単	1.42% (63.95%)	1.17% (42.94%)	1.69% (87.92%)	1.12% (30.67%)	2.55% (51.46%)	2.26% (87.28%)	1.01% (56.36%)	16.05% (65.71%)
総合	56.13% (72.80%)	54.38% (69.30%)	57.60% (76.52%)	60.67% (70.58%)	65.61% (80.36%)	59.85% (75.18%)	53.91% (70.80%)	88.35% (69.53%)

でも、まだまだなモデルでしたorz

追記 2026.10.3 23:39

NumberOfLeaves: 31
NumberOfIterations: 3,000
LearningRate: 0.010
MaximumBinCountPerFeature: 63
MinimumExampleCountPerLeaf: 50
SubsampleFraction: 0.050
FeatureFraction: 0.800
L2Regularization: 0.500

葉の数を更に絞ってみたらR² 0.2371～0.2375だったので0.2375検証すると

2,610R	1点	芝(1,278R)	ダート(1,243R)	障害(89R)	8頭以下(157R)	9～12頭(665R)	13頭以上(1,788R)	多点
単勝	24.02% (76.18%)	24.26% (79.26%)	24.14% (74.30%)	19.10% (57.98%)	32.48% (71.08%)	26.17% (71.20%)	22.48% (78.47%)	53.03% (76.37%)
複勝	55.29% (80.56%)	54.54% (81.55%)	56.23% (80.04%)	52.81% (73.60%)	64.97% (91.08%)	60.45% (81.31%)	52.52% (79.36%)	88.24% (81.03%)
枠連	13.46% (75.75%)	12.41% (72.37%)	14.39% (78.95%)	13.92% (74.30%)	-- (--)	14.44% (71.68%)	12.30% (72.81%)	29.30% (77.29%)
馬連	9.77% (65.36%)	9.47% (67.28%)	10.14% (64.05%)	8.99% (56.18%)	20.38% (97.20%)	11.73% (70.99%)	8.11% (60.47%)	22.91% (74.36%)
ワイド	23.87% (75.13%)	22.38% (71.10%)	25.66% (79.90%)	20.22% (66.52%)	37.58% (72.99%)	27.97% (79.94%)	21.14% (73.53%)	45.36% (78.11%)
馬単	5.17% (59.82%)	5.01% (69.34%)	5.31% (49.77%)	5.62% (63.60%)	10.19% (58.03%)	6.92% (70.32%)	4.08% (56.08%)	22.91% (73.43%)
三連複	6.55% (82.69%)	6.42% (74.92%)	6.76% (89.44%)	5.62% (99.78%)	13.38% (91.02%)	7.22% (87.53%)	5.70% (80.15%)	16.40% (73.56%)
三連単	1.38% (68.10%)	1.25% (59.13%)	1.53% (79.99%)	1.12% (30.67%)	2.55% (51.46%)	2.26% (119.47%)	0.95% (50.45%)	16.40% (67.78%)
総合	56.70% (72.91%)	55.87% (71.86%)	57.68% (74.53%)	55.06% (65.20%)	66.88% (76.12%)	61.35% (81.56%)	54.08% (68.91%)	88.47% (71.85%)

少しは良くなった。まだまだ改善の余地あるか?

相対タイム学習

ここ最近のパラメーターで相対タイム学習に挑んでますが、

NumberOfLeaves: 31
NumberOfIterations: 1,500
LearningRate: 0.050
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 20
SubsampleFraction: 0.500
FeatureFraction: 0.980
L2Regularization: 0.500

これで10回学習させて\(R^{2}\) 0.2288だと

2,610R	1点	芝(1,278R)	ダート(1,243R)	障害(89R)	8頭以下(157R)	9～12頭(665R)	13頭以上(1,788R)	多点
単勝	23.60% (76.21%)	23.71% (79.50%)	23.89% (74.22%)	17.98% (56.74%)	31.85% (67.39%)	26.02% (69.91%)	21.98% (79.32%)	52.80% (76.59%)
複勝	55.02% (81.02%)	53.91% (80.20%)	56.32% (82.34%)	52.81% (74.16%)	64.33% (86.69%)	60.60% (82.24%)	52.13% (80.06%)	88.35% (80.94%)
枠連	12.48% (68.05%)	11.86% (64.13%)	13.12% (72.68%)	11.39% (52.91%)	-- (--)	13.83% (69.47%)	11.24% (63.53%)	28.58% (75.07%)
馬連	9.27% (60.49%)	9.15% (60.52%)	9.49% (61.49%)	7.87% (46.29%)	20.38% (99.04%)	11.28% (69.32%)	7.55% (53.83%)	22.22% (73.03%)
ワイド	23.26% (72.21%)	22.22% (66.60%)	24.54% (78.30%)	20.22% (67.53%)	37.58% (70.06%)	27.97% (80.86%)	20.25% (69.18%)	45.06% (76.93%)
馬単	4.83% (53.25%)	4.46% (55.09%)	5.23% (52.27%)	4.49% (40.45%)	10.83% (88.22%)	6.32% (57.53%)	3.75% (48.59%)	22.22% (70.93%)
三連複	6.25% (76.38%)	5.95% (82.28%)	6.60% (72.81%)	5.62% (41.69%)	11.46% (64.90%)	6.62% (62.47%)	5.65% (82.57%)	15.36% (69.27%)
三連単	1.46% (93.93%)	1.10% (109.68%)	1.77% (78.67%)	2.25% (80.90%)	2.55% (102.04%)	1.80% (50.11%)	1.23% (109.52%)	15.36% (64.91%)
総合	56.21% (72.75%)	54.77% (74.95%)	57.76% (71.59%)	55.06% (57.65%)	66.24% (82.62%)	61.50% (67.74%)	53.36% (73.32%)	88.54% (69.50%)

これを更に精度上げるにはってGeminiにぶつけると、

NumberOfLeaves: 63
NumberOfIterations: 3,000
LearningRate: 0.010
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 20
SubsampleFraction: 0.500
FeatureFraction: 0.800
L2Regularization: 0.500

これを試すと\(R^{2}\) 0.2339

2,610R	1点	芝(1,278R)	ダート(1,243R)	障害(89R)	8頭以下(157R)	9～12頭(665R)	13頭以上(1,788R)	多点
単勝	23.56% (77.59%)	23.47% (82.89%)	24.05% (73.68%)	17.98% (56.07%)	31.85% (68.22%)	25.56% (68.45%)	22.09% (81.81%)	53.75% (78.08%)
複勝	55.13% (80.39%)	53.99% (80.43%)	56.07% (80.26%)	58.43% (81.80%)	63.69% (84.08%)	60.00% (80.48%)	52.57% (80.04%)	88.28% (80.70%)
枠連	13.03% (71.22%)	11.76% (67.45%)	14.23% (75.50%)	12.66% (59.11%)	-- (--)	13.53% (68.15%)	12.08% (68.18%)	29.17% (75.76%)
馬連	9.50% (65.75%)	9.08% (64.98%)	9.98% (67.47%)	8.99% (52.81%)	19.11% (99.75%)	11.13% (66.66%)	8.05% (62.43%)	23.45% (72.81%)
ワイド	23.64% (74.45%)	22.07% (65.40%)	25.34% (84.42%)	22.47% (65.28%)	36.94% (70.96%)	27.07% (75.61%)	21.20% (74.33%)	45.79% (76.73%)
馬単	5.25% (69.81%)	5.09% (79.67%)	5.47% (61.31%)	4.49% (46.85%)	10.83% (92.61%)	6.62% (64.06%)	4.25% (69.94%)	23.45% (72.62%)
三連複	6.32% (75.02%)	6.03% (66.40%)	6.76% (87.28%)	4.49% (27.64%)	12.74% (66.82%)	6.62% (72.09%)	5.65% (76.83%)	15.94% (73.48%)
三連単	1.42% (56.84%)	1.41% (58.73%)	1.45% (56.76%)	1.12% (30.67%)	2.55% (105.73%)	2.26% (73.25%)	1.01% (46.44%)	15.94% (67.97%)
総合	56.36% (71.39%)	55.16% (70.81%)	57.28% (73.32%)	60.67% (52.44%)	66.24% (84.02%)	60.60% (71.09%)	53.91% (70.00%)	88.51% (71.66%)

なんだけど、微妙な検証結果。

AutoMLのパラメーターを真似する

AutoMLのログにモデルをセーブする際にパラメーターを表示する機能追加を先日してあったのですが、それをパクってみようかと(笑)

NumberOfLeaves: 9000
NumberOfIterations: 1,500
LearningRate: 0.003
MaximumBinCountPerFeature: 399
MinimumExampleCountPerLeaf: 23
SubsampleFraction: 0.025
FeatureFraction: 0.980
L2Regularization: 0.500

モデルのRMSE 2.0384で

183R	1点	芝(129R)	ダート(54R)	8頭以下(28R)	9～12頭(68R)	13頭以上(87R)	多点
単勝	24.59% (100.66%)	25.58% (109.46%)	22.22% (79.63%)	35.71% (82.50%)	30.88% (133.09%)	16.09% (81.15%)	48.63% (68.94%)
複勝	51.91% (97.92%)	49.61% (90.93%)	57.41% (114.63%)	60.71% (83.21%)	55.88% (101.47%)	45.98% (99.89%)	81.42% (84.37%)
枠連	9.52% (107.55%)	11.34% (150.10%)	6.00% (25.00%)	-- (--)	16.18% (168.68%)	3.45% (49.89%)	24.49% (105.28%)
馬連	7.65% (98.25%)	9.30% (131.24%)	3.70% (19.44%)	21.43% (151.07%)	8.82% (139.71%)	2.30% (48.85%)	19.13% (106.27%)
ワイド	18.58% (99.62%)	19.38% (76.20%)	16.67% (155.56%)	39.29% (113.93%)	20.59% (85.29%)	10.34% (106.21%)	38.25% (100.00%)
馬単	4.92% (122.40%)	5.43% (161.63%)	3.70% (28.70%)	14.29% (181.43%)	5.88% (241.18%)	1.15% (10.57%)	19.13% (105.73%)
三連複	4.92% (108.03%)	4.65% (70.23%)	5.56% (198.33%)	7.14% (177.86%)	5.88% (60.00%)	3.45% (123.10%)	10.93% (76.99%)
三連単	2.19% (193.77%)	2.33% (212.79%)	1.85% (148.33%)	7.14% (534.29%)	1.47% (183.68%)	1.15% (92.07%)	10.93% (57.91%)
総合	53.55% (116.24%)	51.94% (124.53%)	57.41% (96.87%)	60.71% (189.18%)	60.29% (139.14%)	45.98% (76.47%)	81.42% (75.61%)

で、まあ、基本的には似てる事は似てるけど、通常用走破タイム学習にも試すとそのままではOOMでしたorz 少し抑えて

NumberOfLeaves: 2048
NumberOfIterations: 1,500
LearningRate: 0.003
MaximumBinCountPerFeature: 399
MinimumExampleCountPerLeaf: 100
SubsampleFraction: 0.100
FeatureFraction: 0.980
L2Regularization: 0.500

とするとRMSE 1.6526で

2,427R	1点	芝(1,149R)	ダート(1,189R)	障害(89R)	8頭以下(129R)	9～12頭(597R)	13頭以上(1,701R)	多点
単勝	20.07% (70.88%)	18.80% (74.97%)	20.86% (65.71%)	25.84% (87.08%)	32.56% (78.06%)	20.10% (57.14%)	19.11% (75.16%)	47.88% (76.86%)
複勝	49.61% (81.13%)	45.52% (77.94%)	53.24% (84.03%)	53.93% (83.71%)	61.24% (86.98%)	53.94% (81.19%)	47.21% (80.67%)	85.13% (81.38%)
枠連	11.31% (74.13%)	7.57% (59.33%)	14.50% (87.25%)	12.66% (72.03%)	-- (--)	12.90% (80.69%)	10.11% (67.61%)	25.72% (79.48%)
馬連	7.91% (67.01%)	5.05% (52.28%)	10.43% (79.26%)	11.24% (93.60%)	14.73% (63.72%)	10.05% (88.61%)	6.64% (59.68%)	18.54% (67.49%)
ワイド	20.27% (77.05%)	15.84% (67.57%)	24.31% (86.25%)	23.60% (76.40%)	34.88% (75.74%)	24.79% (89.90%)	17.58% (72.63%)	39.31% (78.52%)
馬単	4.08% (59.40%)	2.26% (47.68%)	5.63% (68.10%)	6.74% (94.61%)	10.08% (102.02%)	5.03% (78.26%)	3.29% (49.55%)	18.54% (66.81%)
三連複	5.03% (68.12%)	3.57% (59.21%)	6.31% (74.71%)	6.74% (95.06%)	10.85% (69.77%)	6.53% (85.93%)	4.06% (61.74%)	12.86% (65.70%)
三連単	1.15% (58.92%)	0.44% (45.44%)	1.85% (74.76%)	1.12% (21.35%)	3.10% (128.99%)	1.68% (70.84%)	0.82% (49.42%)	12.86% (62.07%)
総合	50.76% (69.53%)	46.39% (60.57%)	54.75% (77.45%)	53.93% (78.06%)	62.79% (86.47%)	55.28% (79.07%)	48.27% (64.56%)	85.33% (67.33%)

これではまだまだな感じですね。で、ちょっと調整して

NumberOfLeaves: 512
NumberOfIterations: 1,500
LearningRate: 0.010
MaximumBinCountPerFeature: 399
MinimumExampleCountPerLeaf: 300
SubsampleFraction: 0.300
FeatureFraction: 0.980
L2Regularization: 0.500

だとRMSE 1.5971で

2,427R	1点	芝(1,149R)	ダート(1,189R)	障害(89R)	8頭以下(129R)	9～12頭(597R)	13頭以上(1,701R)	多点
単勝	19.53% (71.52%)	19.15% (73.23%)	19.93% (69.75%)	19.10% (73.15%)	26.36% (76.36%)	21.27% (69.38%)	18.40% (71.90%)	46.89% (76.12%)
複勝	49.07% (82.81%)	45.26% (78.99%)	52.99% (86.88%)	46.07% (77.64%)	56.59% (93.41%)	54.10% (84.57%)	46.74% (81.38%)	83.68% (80.92%)
枠連	10.77% (75.80%)	9.49% (85.54%)	12.11% (70.21%)	7.59% (33.54%)	-- (--)	11.06% (70.90%)	10.05% (73.19%)	23.72% (70.70%)
馬連	6.88% (72.04%)	6.18% (75.66%)	7.65% (70.60%)	5.62% (44.72%)	14.73% (99.38%)	7.20% (68.81%)	6.17% (71.11%)	17.88% (65.14%)
ワイド	19.12% (80.82%)	16.45% (76.34%)	21.78% (87.22%)	17.98% (53.26%)	34.11% (80.78%)	20.44% (74.79%)	17.52% (82.95%)	38.20% (78.41%)
馬単	3.54% (65.43%)	3.31% (76.28%)	3.87% (58.46%)	2.25% (18.65%)	7.75% (73.72%)	4.02% (53.58%)	3.06% (68.97%)	17.88% (63.50%)
三連複	4.70% (78.94%)	4.09% (81.84%)	5.21% (77.01%)	5.62% (67.30%)	15.50% (123.26%)	5.53% (72.36%)	3.59% (77.88%)	11.70% (65.49%)
三連単	0.95% (68.81%)	1.13% (103.38%)	0.76% (38.96%)	1.12% (21.35%)	5.43% (288.99%)	1.17% (65.08%)	0.53% (53.42%)	11.70% (60.32%)
総合	50.60% (74.51%)	46.91% (81.33%)	54.42% (69.88%)	47.19% (48.92%)	60.47% (119.41%)	55.11% (69.94%)	48.27% (72.60%)	83.85% (65.35%)

なんだが、今日はもう遅いので寝ます。また継続してやらなきゃです。

第60回スプリンターズステークス

朝からってか、もう随分と前から色々やってますが、全然時間が足りない。相変わらず、独自に予想してみた。

もうさ、全く予想に集中出来ない状態なので、参加してみただけです。

今週中にはモデルまとめてリリース出来ればと思ってます。

葉の数抑えたランキング学習

ランキング学習では葉の数を多くしてたのですが、ここの所やってる葉の数を抑えたらどうなるかで

NumberOfLeaves: 79
NumberOfIterations: 1500
LearningRate: 0.02
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 30
FeatureFraction: 0.75
SubsampleFraction: 0.8
CustomGains: 0～300 = 0点, 301～1000は0.95乗に0～1000点

[Loop 1] NDCG@1 = 0.7670
[Loop 1] NDCG@3 = 0.7721
[Loop 1] NDCG@5 = 0.7887
[Loop 1] NDCG@10 = 0.8497

2,562R	1点	芝(1,253R)	ダート(1,222R)	障害(87R)	8頭以下(149R)	9～12頭(652R)	13頭以上(1,761R)	多点
単勝	24.63% (73.93%)	24.26% (76.13%)	25.04% (72.77%)	24.14% (58.39%)	32.89% (70.34%)	26.99% (72.75%)	23.06% (74.67%)	54.57% (75.24%)
複勝	55.66% (79.18%)	53.79% (78.00%)	57.20% (80.40%)	60.92% (79.20%)	67.11% (93.69%)	61.81% (80.95%)	52.41% (77.30%)	89.81% (82.08%)
枠連	13.98% (78.51%)	12.56% (83.73%)	15.11% (73.37%)	16.67% (83.72%)	-- (--)	13.04% (64.69%)	13.52% (79.03%)	30.04% (75.87%)
馬連	10.15% (79.92%)	9.58% (100.30%)	10.72% (60.93%)	10.34% (53.22%)	21.48% (94.43%)	10.58% (65.67%)	9.03% (83.97%)	23.26% (72.22%)
ワイド	24.08% (74.39%)	23.06% (77.95%)	25.29% (71.70%)	21.84% (60.80%)	40.27% (82.95%)	26.84% (71.30%)	21.69% (74.80%)	46.84% (74.79%)
馬単	5.70% (91.56%)	5.27% (118.51%)	6.06% (65.49%)	6.90% (69.54%)	11.41% (94.16%)	6.75% (70.32%)	4.83% (99.20%)	23.26% (70.09%)
三連複	6.32% (65.36%)	6.30% (65.83%)	6.46% (67.51%)	4.60% (28.28%)	16.11% (125.57%)	7.21% (63.28%)	5.17% (61.03%)	15.96% (74.27%)
三連単	1.48% (79.04%)	1.36% (96.92%)	1.55% (61.09%)	2.30% (73.68%)	4.03% (226.31%)	2.15% (66.70%)	1.02% (71.15%)	15.96% (70.66%)
総合	57.38% (77.73%)	55.55% (87.23%)	58.92% (69.13%)	62.07% (63.09%)	69.80% (112.49%)	62.27% (69.46%)	54.51% (77.64%)	90.05% (72.50%)

まあ、試しの1回でなので悪くないかな。

NumberOfLeaves: 63
NumberOfIterations: 1500
LearningRate: 0.02
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 30
FeatureFraction: 0.75
SubsampleFraction: 0.8
CustomGains: 0～300 = 0点, 301～1000は0.95乗に0～1000点

[Loop 1] NDCG@1 = 0.7655
[Loop 1] NDCG@3 = 0.7712
[Loop 1] NDCG@5 = 0.7883
[Loop 1] NDCG@10 = 0.8494

2,562R	1点	芝(1,253R)	ダート(1,222R)	障害(87R)	8頭以下(149R)	9～12頭(652R)	13頭以上(1,761R)	多点
単勝	23.93% (72.47%)	23.70% (74.45%)	24.14% (71.29%)	24.14% (60.46%)	32.21% (68.79%)	25.92% (68.27%)	22.49% (74.33%)	54.41% (74.75%)
複勝	55.54% (79.34%)	53.87% (78.22%)	56.71% (80.25%)	63.22% (82.76%)	64.43% (90.87%)	61.50% (80.54%)	52.58% (77.93%)	89.38% (81.20%)
枠連	13.77% (77.66%)	12.46% (80.48%)	14.94% (75.97%)	14.10% (64.23%)	-- (--)	13.19% (62.33%)	13.17% (78.79%)	29.48% (75.34%)
馬連	9.88% (65.17%)	9.34% (70.04%)	10.47% (61.50%)	9.20% (46.67%)	22.82% (100.81%)	10.89% (64.57%)	8.40% (62.38%)	23.15% (71.05%)
ワイド	24.32% (71.61%)	23.38% (69.49%)	25.45% (73.78%)	21.84% (71.61%)	41.61% (79.06%)	27.61% (74.05%)	21.64% (70.07%)	46.92% (75.69%)
馬単	5.23% (58.90%)	4.87% (62.96%)	5.56% (54.35%)	5.75% (64.14%)	10.74% (69.87%)	6.75% (71.37%)	4.20% (53.35%)	23.15% (68.93%)
三連複	6.52% (69.76%)	6.30% (63.72%)	6.87% (78.91%)	4.60% (28.28%)	14.09% (74.70%)	7.52% (63.90%)	5.51% (71.52%)	16.12% (74.53%)
三連単	1.37% (97.92%)	0.88% (64.64%)	1.80% (133.76%)	2.30% (73.68%)	2.01% (30.94%)	1.99% (62.06%)	1.08% (116.86%)	16.12% (72.10%)
総合	57.42% (74.06%)	55.95% (70.31%)	58.43% (78.74%)	64.37% (61.44%)	67.11% (73.58%)	62.27% (68.38%)	54.80% (75.65%)	89.62% (72.96%)

葉の数削り過ぎかな^^; では、葉の数は戻して葉の最小少し増やして

NumberOfLeaves: 79
NumberOfIterations: 1500
LearningRate: 0.02
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 50
FeatureFraction: 0.75
SubsampleFraction: 0.8
CustomGains: 0～300 = 0点, 301～1000は0.95乗に0～1000点

[Loop 1] NDCG@1 = 0.7663
[Loop 1] NDCG@3 = 0.7719
[Loop 1] NDCG@5 = 0.7887
[Loop 1] NDCG@10 = 0.8496

2,562R	1点	芝(1,253R)	ダート(1,222R)	障害(87R)	8頭以下(149R)	9～12頭(652R)	13頭以上(1,761R)	多点
単勝	24.24% (72.94%)	23.86% (75.23%)	24.63% (71.57%)	24.14% (59.31%)	34.23% (76.78%)	25.92% (68.48%)	22.77% (74.27%)	54.72% (75.58%)
複勝	55.19% (78.78%)	53.15% (77.09%)	56.79% (80.25%)	62.07% (82.53%)	64.43% (88.66%)	60.89% (79.60%)	52.30% (77.64%)	89.66% (81.92%)
枠連	13.98% (79.62%)	12.65% (83.57%)	15.02% (75.54%)	16.67% (86.67%)	-- (--)	13.34% (62.18%)	13.40% (81.43%)	30.52% (76.57%)
馬連	10.27% (80.00%)	9.74% (97.04%)	10.72% (63.46%)	11.49% (66.90%)	23.49% (100.94%)	10.89% (63.88%)	8.92% (84.20%)	23.54% (71.50%)
ワイド	24.20% (72.74%)	23.30% (73.81%)	25.37% (72.81%)	20.69% (56.32%)	40.94% (78.66%)	27.61% (71.26%)	21.52% (72.78%)	46.99% (76.75%)
馬単	5.85% (88.86%)	5.35% (117.88%)	6.22% (59.71%)	8.05% (80.34%)	13.42% (108.86%)	6.90% (71.72%)	4.83% (93.51%)	23.54% (69.61%)
三連複	6.83% (80.21%)	6.30% (68.83%)	7.45% (90.32%)	5.75% (102.07%)	14.77% (103.22%)	8.13% (85.74%)	5.68% (76.22%)	16.28% (75.35%)
三連単	1.60% (118.35%)	1.20% (82.79%)	1.96% (158.00%)	2.30% (73.68%)	4.03% (181.95%)	1.99% (115.28%)	1.25% (114.11%)	16.28% (72.53%)
総合	57.14% (83.99%)	55.31% (84.55%)	58.59% (84.01%)	63.22% (75.84%)	67.11% (105.58%)	61.66% (77.27%)	54.63% (84.27%)	89.89% (73.58%)

指数的には落ちた感じだけど、三連系が良くなった。葉の最小を減らすと

NumberOfLeaves: 79
NumberOfIterations: 1500
LearningRate: 0.02
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 20
FeatureFraction: 0.75
SubsampleFraction: 0.8
CustomGains: 0～300 = 0点, 301～1000は0.95乗に0～1000点

[Loop 1] NDCG@1 = 0.7643
[Loop 1] NDCG@3 = 0.7715
[Loop 1] NDCG@5 = 0.7885
[Loop 1] NDCG@10 = 0.8492

2,562R	1点	芝(1,253R)	ダート(1,222R)	障害(87R)	8頭以下(149R)	9～12頭(652R)	13頭以上(1,761R)	多点
単勝	24.12% (73.38%)	23.54% (73.97%)	24.80% (74.19%)	22.99% (53.56%)	31.54% (68.26%)	26.23% (67.41%)	22.71% (76.03%)	54.92% (76.85%)
複勝	55.85% (79.85%)	53.47% (77.55%)	57.69% (81.90%)	64.37% (84.25%)	65.77% (91.21%)	61.96% (80.84%)	52.75% (78.52%)	89.73% (81.45%)
枠連	13.55% (75.87%)	11.62% (74.15%)	15.02% (76.64%)	17.95% (88.08%)	-- (--)	12.42% (59.95%)	13.17% (77.33%)	29.70% (75.77%)
馬連	10.03% (80.70%)	8.94% (93.68%)	11.05% (68.65%)	11.49% (63.10%)	22.15% (102.15%)	10.28% (63.60%)	8.92% (85.22%)	23.34% (72.45%)
ワイド	24.28% (74.84%)	22.75% (74.03%)	26.02% (75.86%)	21.84% (72.07%)	37.58% (70.54%)	27.76% (75.38%)	21.86% (75.00%)	46.45% (75.40%)
馬単	5.39% (83.65%)	4.55% (106.00%)	6.14% (62.36%)	6.90% (60.80%)	11.41% (107.65%)	5.98% (58.54%)	4.66% (90.92%)	23.34% (70.37%)
三連複	6.60% (74.05%)	6.46% (74.87%)	6.87% (76.46%)	4.60% (28.28%)	15.44% (122.62%)	7.82% (75.90%)	5.39% (69.25%)	16.47% (77.54%)
三連単	1.48% (74.33%)	1.04% (52.14%)	1.96% (100.14%)	1.15% (31.38%)	4.03% (226.31%)	1.84% (110.41%)	1.14% (48.11%)	16.47% (73.15%)
総合	57.53% (77.10%)	55.39% (78.38%)	59.17% (77.03%)	65.52% (59.83%)	68.46% (112.67%)	62.42% (74.01%)	54.80% (75.05%)	89.93% (74.14%)

ダメだ(笑) 葉の最小は30～50の間辺りが良いのかな? もしくはそれ以上かも?

NumberOfLeaves: 79
NumberOfIterations: 1500
LearningRate: 0.02
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 40
FeatureFraction: 0.75
SubsampleFraction: 0.8
CustomGains: 0～300 = 0点, 301～1000は0.95乗に0～1000点

[Loop 1] NDCG@1 = 0.7653
[Loop 1] NDCG@3 = 0.7717
[Loop 1] NDCG@5 = 0.7882
[Loop 1] NDCG@10 = 0.8495

2,562R	1点	芝(1,253R)	ダート(1,222R)	障害(87R)	8頭以下(149R)	9～12頭(652R)	13頭以上(1,761R)	多点
単勝	24.75% (75.39%)	24.34% (76.37%)	25.20% (75.30%)	24.14% (62.41%)	32.89% (70.20%)	26.38% (71.35%)	23.45% (77.32%)	54.49% (74.58%)
複勝	56.01% (79.90%)	54.51% (79.60%)	57.04% (79.96%)	63.22% (83.33%)	64.43% (88.93%)	61.04% (80.75%)	53.44% (78.82%)	89.73% (80.79%)
枠連	13.55% (75.94%)	11.90% (78.15%)	14.76% (73.10%)	17.95% (88.08%)	-- (--)	12.27% (54.48%)	13.23% (79.44%)	29.61% (73.36%)
馬連	9.84% (76.41%)	8.86% (92.39%)	10.72% (60.96%)	11.49% (63.10%)	20.81% (94.30%)	9.97% (56.46%)	8.86% (82.28%)	23.11% (69.01%)
ワイド	23.97% (74.15%)	22.67% (75.43%)	25.53% (74.19%)	20.69% (55.06%)	38.93% (76.51%)	26.07% (68.62%)	21.92% (75.99%)	46.29% (73.34%)
馬単	5.62% (84.50%)	4.79% (105.78%)	6.38% (63.35%)	6.90% (75.29%)	12.75% (102.89%)	6.29% (63.71%)	4.77% (90.65%)	23.11% (67.00%)
三連複	6.44% (70.12%)	6.07% (60.97%)	6.87% (82.05%)	5.75% (34.48%)	13.42% (71.74%)	7.52% (63.34%)	5.45% (72.50%)	16.35% (72.69%)
三連単	1.41% (103.43%)	1.04% (72.38%)	1.72% (137.39%)	2.30% (73.68%)	2.68% (86.85%)	1.53% (50.09%)	1.25% (124.58%)	16.35% (69.08%)
総合	57.53% (80.03%)	56.19% (80.17%)	58.51% (80.83%)	63.22% (66.65%)	67.11% (84.49%)	61.35% (63.60%)	55.31% (85.20%)	89.85% (70.67%)

中途半端はダメか? まあ、実際1発勝負だと的確には分からないけど^^; 秋のGIには間に合えばと頑張ったつもりが、既に今日はスプリンターズorz

NumberOfLeaves: 79
NumberOfIterations: 1500
LearningRate: 0.02
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 80
FeatureFraction: 0.75
SubsampleFraction: 0.8
CustomGains: 0～300 = 0点, 301～1000は0.95乗に0～1000点

[Loop 1] NDCG@1 = 0.7650
[Loop 1] NDCG@3 = 0.7717
[Loop 1] NDCG@5 = 0.7882
[Loop 1] NDCG@10 = 0.8494

2,562R	1点	芝(1,253R)	ダート(1,222R)	障害(87R)	8頭以下(149R)	9～12頭(652R)	13頭以上(1,761R)	多点
単勝	24.16% (72.86%)	24.42% (76.91%)	24.06% (70.28%)	21.84% (50.92%)	34.23% (74.30%)	25.92% (70.08%)	22.66% (73.78%)	54.57% (74.85%)
複勝	55.78% (79.55%)	54.11% (79.02%)	57.12% (80.10%)	60.92% (79.43%)	65.77% (94.03%)	61.35% (80.66%)	52.87% (77.91%)	89.11% (81.29%)
枠連	13.90% (77.75%)	12.28% (77.35%)	15.11% (77.69%)	17.95% (84.10%)	-- (--)	12.73% (58.79%)	13.52% (80.22%)	30.13% (76.80%)
馬連	9.88% (64.86%)	9.10% (70.14%)	10.56% (59.74%)	11.49% (60.69%)	22.15% (100.87%)	9.97% (57.59%)	8.80% (64.50%)	23.61% (69.94%)
ワイド	24.16% (70.86%)	22.67% (69.15%)	25.86% (72.64%)	21.84% (70.69%)	40.27% (78.79%)	26.84% (70.81%)	21.81% (70.21%)	46.80% (75.25%)
馬単	5.35% (61.32%)	4.95% (64.60%)	5.81% (59.11%)	4.60% (44.94%)	12.75% (91.81%)	5.98% (61.96%)	4.49% (58.50%)	23.61% (67.96%)
三連複	6.87% (75.59%)	6.38% (64.95%)	7.53% (89.86%)	4.60% (28.28%)	15.44% (95.91%)	7.98% (67.75%)	5.74% (76.77%)	16.24% (66.85%)
三連単	1.44% (109.13%)	0.96% (69.47%)	1.96% (155.33%)	1.15% (31.38%)	3.36% (101.54%)	1.69% (51.66%)	1.19% (131.05%)	16.24% (62.08%)
総合	57.46% (76.47%)	56.03% (71.34%)	58.59% (83.12%)	62.07% (55.94%)	68.46% (91.04%)	61.81% (64.91%)	54.91% (79.12%)	89.31% (67.24%)

結局は葉の最小は50が一番良いのかな? 一応60も試して置くか。

NumberOfLeaves: 79
NumberOfIterations: 1500
LearningRate: 0.02
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 60
FeatureFraction: 0.75
SubsampleFraction: 0.8
CustomGains: 0～300 = 0点, 301～1000は0.95乗に0～1000点

[Loop 1] NDCG@1 = 0.7653
[Loop 1] NDCG@3 = 0.7719
[Loop 1] NDCG@5 = 0.7884
[Loop 1] NDCG@10 = 0.8495

2,562R	1点	芝(1,253R)	ダート(1,222R)	障害(87R)	8頭以下(149R)	9～12頭(652R)	13頭以上(1,761R)	多点
単勝	24.20% (73.68%)	23.78% (75.19%)	24.71% (73.46%)	22.99% (54.94%)	32.21% (68.39%)	25.77% (67.12%)	22.94% (76.55%)	54.96% (75.45%)
複勝	55.58% (79.21%)	54.03% (78.53%)	56.71% (79.78%)	62.07% (80.92%)	67.79% (97.99%)	61.35% (79.08%)	52.41% (77.67%)	89.38% (81.36%)
枠連	13.85% (77.27%)	12.00% (74.07%)	15.45% (80.23%)	15.38% (76.92%)	-- (--)	12.58% (56.58%)	13.52% (80.41%)	30.13% (75.59%)
馬連	10.11% (69.30%)	8.94% (67.17%)	11.29% (72.38%)	10.34% (56.55%)	20.13% (91.95%)	10.12% (58.30%)	9.26% (71.45%)	23.46% (73.07%)
ワイド	24.12% (72.28%)	22.59% (67.57%)	25.70% (76.69%)	24.14% (78.16%)	38.93% (72.82%)	25.31% (65.89%)	22.43% (74.60%)	46.68% (76.77%)
馬単	5.35% (63.47%)	4.47% (58.80%)	6.30% (69.61%)	4.60% (44.60%)	9.40% (64.90%)	5.52% (55.55%)	4.94% (66.29%)	23.46% (71.13%)
三連複	6.87% (80.10%)	6.62% (77.24%)	7.20% (84.27%)	5.75% (62.64%)	14.77% (119.33%)	7.36% (68.39%)	6.02% (81.11%)	16.16% (75.00%)
三連単	1.41% (104.04%)	0.96% (77.64%)	1.88% (136.28%)	1.15% (31.38%)	2.68% (170.20%)	1.69% (53.77%)	1.19% (117.05%)	16.16% (71.37%)
総合	57.34% (77.42%)	55.87% (71.99%)	58.43% (84.11%)	63.22% (60.55%)	70.47% (97.94%)	61.96% (63.08%)	54.51% (80.64%)	89.62% (73.17%)

何とも微妙な結果だ。まあ、50で更に攻めるかな。

本日の通常用走破タイム学習

時間的には12時間と本来やりたい24時間の半分ですがRMSE 1.6106で

2,387R	1点	芝(1,130R)	ダート(1,170R)	障害(87R)	8頭以下(121R)	9～12頭(586R)	13頭以上(1,680R)	多点
単勝	20.61% (82.58%)	20.35% (76.86%)	21.11% (89.91%)	17.24% (58.51%)	30.58% (85.87%)	22.01% (70.03%)	19.40% (86.73%)	48.30% (76.59%)
複勝	50.27% (81.72%)	47.52% (76.51%)	52.99% (87.10%)	49.43% (77.01%)	66.12% (101.40%)	54.61% (83.62%)	47.62% (79.64%)	85.71% (81.67%)
枠連	10.41% (71.55%)	9.32% (58.71%)	11.73% (86.45%)	5.13% (18.85%)	-- (--)	10.75% (59.98%)	9.70% (71.54%)	25.01% (77.98%)
馬連	7.79% (67.15%)	7.08% (61.12%)	8.55% (72.26%)	6.90% (76.67%)	17.36% (96.45%)	8.87% (67.58%)	6.73% (64.89%)	18.43% (64.58%)
ワイド	20.03% (70.86%)	18.76% (67.65%)	21.45% (73.41%)	17.24% (78.28%)	34.71% (84.46%)	23.55% (71.59%)	17.74% (69.63%)	40.09% (78.79%)
馬単	4.15% (65.82%)	3.98% (65.93%)	4.44% (65.19%)	2.30% (72.87%)	10.74% (117.02%)	4.44% (53.57%)	3.57% (66.40%)	18.43% (62.32%)
三連複	4.82% (58.62%)	4.34% (45.55%)	5.47% (73.44%)	2.30% (28.97%)	13.22% (59.09%)	4.61% (36.60%)	4.29% (66.26%)	11.98% (69.51%)
三連単	1.09% (49.29%)	0.88% (36.97%)	1.37% (64.85%)	0.00% (0.00%)	1.65% (19.59%)	0.68% (24.22%)	1.19% (60.18%)	11.98% (68.50%)
総合	51.32% (68.41%)	48.67% (61.20%)	54.02% (76.52%)	49.43% (51.82%)	67.77% (80.55%)	55.12% (58.40%)	48.81% (70.66%)	86.13% (70.02%)

目指す精度にはまだまだな感じですorz あまりお薦めではないけど、並行して相対タイム学習を3時間程したのは\(R^{2}\) 0.2107で

2,562R	1点	芝(1,253R)	ダート(1,222R)	障害(87R)	8頭以下(149R)	9～12頭(652R)	13頭以上(1,761R)	多点
単勝	24.20% (79.70%)	23.86% (81.72%)	25.12% (80.77%)	16.09% (35.75%)	31.54% (68.39%)	25.92% (73.25%)	22.94% (83.05%)	52.22% (76.43%)
複勝	54.45% (82.13%)	53.55% (83.88%)	55.32% (80.49%)	55.17% (79.89%)	63.09% (89.40%)	58.74% (81.87%)	52.13% (81.61%)	87.94% (81.36%)
枠連	12.60% (76.43%)	11.34% (77.25%)	13.91% (75.55%)	10.26% (78.21%)	-- (--)	13.34% (74.49%)	11.58% (72.67%)	27.53% (73.74%)
馬連	8.90% (64.64%)	8.46% (62.57%)	9.33% (65.77%)	9.20% (78.74%)	18.79% (78.32%)	11.04% (77.44%)	7.27% (58.75%)	21.39% (65.36%)
ワイド	23.15% (82.73%)	22.27% (82.06%)	24.30% (84.44%)	19.54% (68.28%)	36.91% (81.01%)	27.61% (79.29%)	20.33% (84.15%)	44.30% (78.19%)
馬単	4.92% (64.09%)	4.39% (65.32%)	5.48% (64.19%)	4.60% (44.94%)	10.07% (51.68%)	6.44% (77.50%)	3.92% (60.17%)	21.39% (62.04%)
三連複	6.05% (78.77%)	6.46% (87.04%)	5.73% (73.89%)	4.60% (28.28%)	14.09% (90.74%)	7.21% (79.36%)	4.94% (77.54%)	14.99% (69.95%)
三連単	1.05% (65.77%)	1.12% (69.93%)	0.98% (63.96%)	1.15% (31.38%)	2.68% (58.46%)	1.84% (72.78%)	0.62% (63.80%)	14.99% (64.31%)
総合	55.97% (74.26%)	55.23% (76.20%)	56.79% (73.62%)	55.17% (55.39%)	65.10% (74.00%)	59.66% (77.00%)	53.83% (72.72%)	88.25% (67.71%)

これはまあ、更に学習時間が短か過ぎたかなぁ。

で、ここで手動でパラメーター設定してLightGBMを試すと

NumberOfLeaves: 79
NumberOfIterations: 1,500
LearningRate: 0.020
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 30
SubsampleFraction: 0.025
FeatureFraction: 0.980
L2Regularization: 0.500

通常用走破タイム学習はRMSE 1.6010で

2,387R	1点	芝(1,130R)	ダート(1,170R)	障害(87R)	8頭以下(121R)	9～12頭(586R)	13頭以上(1,680R)	多点
単勝	19.02% (72.64%)	19.03% (84.56%)	19.57% (63.01%)	11.49% (47.47%)	23.14% (65.62%)	21.84% (74.08%)	17.74% (72.65%)	48.14% (76.86%)
複勝	48.47% (79.81%)	46.46% (83.96%)	50.34% (76.58%)	49.43% (69.20%)	61.16% (97.36%)	53.07% (83.36%)	45.95% (77.30%)	85.13% (80.85%)
枠連	11.29% (75.40%)	10.25% (85.83%)	12.44% (68.62%)	7.69% (41.92%)	-- (--)	12.12% (75.53%)	10.36% (71.09%)	26.07% (76.71%)
馬連	7.79% (71.94%)	6.64% (78.00%)	8.97% (67.42%)	6.90% (53.91%)	15.70% (64.63%)	9.04% (80.02%)	6.79% (69.64%)	18.01% (64.85%)
ワイド	20.70% (84.82%)	18.50% (84.18%)	22.82% (83.47%)	20.69% (111.26%)	33.88% (62.98%)	23.55% (85.32%)	18.75% (86.21%)	39.72% (76.99%)
馬単	3.39% (68.24%)	3.19% (91.26%)	3.85% (51.09%)	0.00% (0.00%)	6.61% (68.68%)	4.61% (71.28%)	2.74% (67.15%)	18.01% (62.55%)
三連複	4.78% (82.71%)	3.45% (104.03%)	6.07% (65.74%)	4.60% (34.02%)	6.61% (33.88%)	5.29% (53.75%)	4.46% (96.33%)	12.69% (60.15%)
三連単	0.88% (107.72%)	0.80% (190.78%)	1.03% (35.50%)	0.00% (0.00%)	1.65% (57.44%)	1.19% (38.72%)	0.71% (135.40%)	12.69% (56.99%)
総合	49.85% (80.47%)	48.05% (100.58%)	51.62% (63.90%)	49.43% (44.76%)	62.81% (64.37%)	54.61% (70.26%)	47.26% (84.47%)	85.55% (63.40%)

相対タイム学習は\(R^{2}\) 0.2290で

2,562R	1点	芝(1,253R)	ダート(1,222R)	障害(87R)	8頭以下(149R)	9～12頭(652R)	13頭以上(1,761R)	多点
単勝	24.08% (78.40%)	24.02% (80.99%)	24.47% (76.32%)	19.54% (70.23%)	34.90% (76.71%)	25.31% (68.44%)	22.71% (82.23%)	53.32% (77.31%)
複勝	55.43% (81.24%)	53.79% (80.37%)	56.79% (81.72%)	59.77% (87.13%)	64.43% (86.04%)	59.82% (81.52%)	53.04% (80.73%)	88.41% (81.41%)
枠連	12.38% (64.41%)	11.62% (60.44%)	13.05% (67.97%)	12.82% (65.51%)	-- (--)	13.96% (69.68%)	11.07% (58.69%)	28.74% (79.15%)
馬連	9.29% (60.80%)	8.86% (56.62%)	9.82% (65.88%)	8.05% (49.77%)	19.46% (92.75%)	11.66% (70.84%)	7.55% (54.38%)	22.29% (69.34%)
ワイド	22.87% (70.94%)	21.23% (62.50%)	24.63% (79.10%)	21.84% (77.82%)	37.58% (70.07%)	27.30% (76.32%)	19.99% (69.02%)	45.36% (76.88%)
馬単	5.62% (64.47%)	5.35% (64.54%)	5.89% (65.22%)	5.75% (52.99%)	12.08% (92.48%)	7.21% (65.09%)	4.49% (61.87%)	22.29% (68.06%)
三連複	6.21% (67.11%)	5.91% (62.48%)	6.55% (73.59%)	5.75% (42.64%)	12.75% (62.82%)	6.75% (56.66%)	5.45% (71.34%)	15.42% (71.89%)
三連単	1.56% (61.32%)	1.28% (52.16%)	1.80% (69.19%)	2.30% (82.76%)	2.68% (84.77%)	2.61% (98.70%)	1.08% (45.50%)	15.42% (65.67%)
総合	56.67% (68.64%)	55.23% (65.10%)	57.77% (72.40%)	62.07% (66.11%)	66.44% (80.81%)	60.74% (73.40%)	54.34% (65.47%)	88.68% (69.80%)

どちらも10分程度で学習した結果なので、AutoMLで長時間するのが良いのか、パラメーターを探り当てる方が良いのかだなぁ。この辺りの機能追加で最近時間取られてたので、もう少しモデル探しを頑張るか。

昨夜学習させた新馬戦用モデル

昨夜寝る前に3時間×2回の新馬戦用走破タイム学習では2回とも同じRMSE 2.0408で

171R	1点	芝(120R)	ダート(51R)	8頭以下(27R)	9～12頭(65R)	13頭以上(79R)	多点
単勝	25.73% (110.64%)	28.33% (124.50%)	19.61% (78.04%)	33.33% (75.56%)	30.77% (125.85%)	18.99% (110.13%)	47.37% (71.15%)
複勝	55.56% (106.08%)	55.00% (102.00%)	56.86% (115.69%)	62.96% (102.96%)	58.46% (100.62%)	50.63% (111.65%)	81.87% (87.43%)
枠連	11.76% (165.37%)	13.48% (230.11%)	8.51% (42.77%)	-- (--)	13.85% (153.54%)	8.86% (158.35%)	28.68% (110.32%)
馬連	8.19% (130.64%)	10.00% (177.42%)	3.92% (20.59%)	22.22% (142.59%)	6.15% (125.08%)	5.06% (131.14%)	19.88% (92.44%)
ワイド	18.71% (156.14%)	21.67% (170.75%)	11.76% (121.76%)	40.74% (111.85%)	20.00% (224.62%)	10.13% (114.94%)	38.60% (116.47%)
馬単	4.68% (213.80%)	5.83% (299.42%)	1.96% (12.35%)	11.11% (32.22%)	3.08% (213.69%)	3.80% (275.95%)	19.88% (84.48%)
三連複	5.85% (121.93%)	5.83% (93.08%)	5.88% (189.80%)	11.11% (223.70%)	6.15% (65.38%)	3.80% (133.67%)	11.11% (63.11%)
三連単	0.58% (7.54%)	0.83% (10.75%)	0.00% (0.00%)	3.70% (47.78%)	0.00% (0.00%)	0.00% (0.00%)	11.11% (43.13%)
総合	57.89% (125.50%)	57.50% (148.36%)	58.82% (72.92%)	62.96% (105.24%)	63.08% (126.10%)	51.90% (129.48%)	81.87% (65.15%)

これ、まあ、想定内なんだが、学習データは2004年～2025年に変え、検証は当然のその後の今年初めから先週末、あっ、今回は末じゃないか、火曜日まで代替開催あったんだった^^;

175R	1点	芝(123R)	ダート(52R)	8頭以下(28R)	9～12頭(66R)	13頭以上(81R)	多点
単勝	25.14% (108.11%)	27.64% (121.46%)	19.23% (76.54%)	32.14% (72.86%)	30.30% (123.94%)	18.52% (107.41%)	48.00% (71.89%)
複勝	55.43% (105.09%)	55.28% (101.54%)	55.77% (113.46%)	64.29% (103.57%)	59.09% (101.06%)	49.38% (108.89%)	82.29% (87.18%)
枠連	11.51% (161.80%)	13.19% (225.05%)	8.33% (41.88%)	-- (--)	13.64% (151.21%)	8.64% (154.44%)	28.06% (107.75%)
馬連	8.00% (127.66%)	9.76% (173.09%)	3.85% (20.19%)	21.43% (137.50%)	6.06% (123.18%)	4.94% (127.90%)	20.00% (91.37%)
ワイド	18.86% (154.23%)	21.95% (168.94%)	11.54% (119.42%)	39.29% (107.86%)	21.21% (225.61%)	9.88% (112.10%)	38.86% (114.90%)
馬単	4.57% (208.91%)	5.69% (292.11%)	1.92% (12.12%)	10.71% (31.07%)	3.03% (210.45%)	3.70% (269.14%)	20.00% (83.90%)
三連複	5.71% (119.14%)	5.69% (90.81%)	5.77% (186.15%)	10.71% (215.71%)	6.06% (64.39%)	3.70% (130.37%)	10.86% (61.67%)
三連単	0.57% (7.37%)	0.81% (10.49%)	0.00% (0.00%)	3.57% (46.07%)	0.00% (0.00%)	0.00% (0.00%)	10.86% (42.14%)
総合	57.71% (123.04%)	57.72% (145.35%)	57.69% (71.50%)	64.29% (102.09%)	63.64% (124.98%)	50.62% (126.28%)	82.29% (64.21%)

それ程変わらないが、話を正確にね(笑) いや、以前2004年～2024年学習させて2025年で検証したら異常に回収率が良かったって事で、更に2026年になると回収率が落ちてたのを踏まえ、では、なるべく直近まで学習させた後が成績良いんならって事で今回やった訳です。まあ、実戦でどうなるかなんだけど^^;

DuckDuckGo AI Chat

今朝昨夜の続きの質問をCopilotにぶつけると「1日の上限に達しました。...」とまあ多分課金を促してるんだと思うけど、まあ、だからあえてそれ以上は使うの止めた(笑) 確かにGeminiでも似た感じなので、Geminiに質問として無料で無制限に使えるのはあるか問合わせるとDuckDuckGo AI Chatがあるよって教えてくれた。なので、しばらくはこれにお世話になってみようかと思う。

直近の相対タイム学習

あれもこれも試してるんですが、昨日やった相対タイム学習の\(R^{2}\)=0.2286は

2,538R	1点	芝(1,241R)	ダート(1,211R)	障害(86R)	8頭以下(147R)	9～12頭(645R)	13頭以上(1,746R)	多点
単勝	23.96% (74.36%)	23.61% (74.60%)	24.77% (75.52%)	17.44% (54.42%)	36.05% (77.55%)	24.96% (71.75%)	22.57% (75.05%)	53.55% (77.58%)
複勝	54.89% (79.39%)	53.34% (78.53%)	56.56% (80.68%)	53.49% (73.72%)	63.95% (85.17%)	59.38% (81.32%)	52.46% (78.19%)	88.57% (80.66%)
枠連	12.67% (65.38%)	12.03% (64.91%)	13.25% (65.75%)	12.99% (66.36%)	-- (--)	13.64% (63.98%)	11.57% (62.04%)	28.85% (75.76%)
馬連	9.57% (61.47%)	9.27% (60.67%)	9.99% (63.09%)	8.14% (50.35%)	21.09% (97.89%)	11.16% (65.05%)	8.02% (57.08%)	22.54% (68.56%)
ワイド	23.01% (70.37%)	21.19% (61.15%)	24.94% (79.17%)	22.09% (79.42%)	40.14% (77.01%)	26.20% (72.05%)	20.39% (69.19%)	45.11% (74.73%)
馬単	5.36% (55.20%)	5.40% (66.12%)	5.37% (44.48%)	4.65% (48.49%)	12.93% (92.45%)	6.82% (68.34%)	4.18% (47.21%)	22.54% (67.43%)
三連複	6.26% (70.87%)	6.04% (67.89%)	6.61% (76.94%)	4.65% (28.60%)	12.93% (63.81%)	6.05% (57.40%)	5.78% (76.45%)	15.25% (60.63%)
三連単	1.42% (56.11%)	1.45% (66.89%)	1.40% (46.79%)	1.16% (31.74%)	2.72% (85.92%)	1.86% (68.50%)	1.15% (49.02%)	15.25% (57.55%)
総合	56.11% (66.66%)	54.71% (67.65%)	57.56% (66.56%)	55.81% (53.98%)	65.31% (82.83%)	60.31% (68.55%)	53.78% (64.28%)	88.77% (64.39%)

取り立てて良いモデルかは微妙なんですが、酷いわけじゃない。これ、もう少し良くしたいと思い、

NumberOfLeaves: 63
NumberOfIterations: 700
LearningRate: 0.020
MaximumBinCountPerFeature: 127
MinimumExampleCountPerLeaf: 20

だと\(R^{2}\)=0.2332で

2,538R	1点	芝(1,241R)	ダート(1,211R)	障害(86R)	8頭以下(147R)	9～12頭(645R)	13頭以上(1,746R)	多点
単勝	24.07% (75.62%)	23.85% (76.95%)	24.69% (75.52%)	18.60% (58.02%)	36.73% (77.89%)	25.27% (70.93%)	22.57% (77.16%)	52.88% (75.42%)
複勝	55.91% (81.42%)	54.47% (81.48%)	57.47% (81.75%)	54.65% (75.81%)	66.67% (91.56%)	59.07% (80.06%)	53.84% (81.07%)	87.90% (80.39%)
枠連	13.46% (75.46%)	12.41% (73.91%)	14.20% (76.16%)	16.88% (86.23%)	-- (--)	13.95% (67.13%)	12.49% (74.08%)	28.58% (73.12%)
馬連	9.65% (65.71%)	9.27% (65.02%)	9.91% (66.17%)	11.63% (69.07%)	20.41% (95.71%)	11.32% (65.80%)	8.13% (63.14%)	22.26% (67.34%)
ワイド	23.72% (73.49%)	21.92% (66.45%)	25.60% (80.74%)	23.26% (73.02%)	38.10% (74.83%)	27.60% (76.67%)	21.08% (72.21%)	45.19% (76.56%)
馬単	5.08% (55.57%)	4.83% (61.13%)	5.28% (48.67%)	5.81% (72.44%)	10.88% (71.63%)	6.82% (62.71%)	3.95% (51.58%)	22.26% (66.41%)
三連複	6.42% (76.94%)	6.37% (72.76%)	6.52% (79.36%)	5.81% (103.26%)	12.93% (92.65%)	7.60% (90.82%)	5.44% (70.49%)	15.41% (72.38%)
三連単	1.38% (61.52%)	1.21% (69.07%)	1.57% (55.90%)	1.16% (31.74%)	2.72% (116.39%)	2.17% (82.64%)	0.97% (49.10%)	15.41% (68.30%)
総合	57.17% (70.66%)	55.68% (70.79%)	58.71% (70.50%)	56.98% (71.00%)	67.35% (88.67%)	60.16% (74.59%)	55.21% (67.35%)	88.18% (70.30%)

少し改善してますね。

ここで、ちょっと気にしてる葉の数なんだけど、極端に少ないのに気が付いた人はここまでの記事をしっかり読んでくれてる方だと思います。今回、Copilotが提案したパラメーターなんです。