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?