Я пытаюсь построить модель регрессии гребня с помощью GridSearchCV, чтобы найти наилучшие значения альфа.
Ниже приведены параметры и результаты модели. Я могу получить лучшее значение и лучший результат, используя _bestparams_ и _bestscr_. Лучшая альфа равна 0,001 согласно моему набору данных.
Мой вопрос: как мне достичь оптимальных значений альфа (0,001) mean_test_score и std_test_score?
ridgeRegressor.cv_result_.["mean_test_score"] приносит значения, но я не могу указать, чьи значения. Как я могу это сделать? Каждый альфа-параметр имеет одинаковые значения mean_test_score и std_test_score.
'params': [{'alpha': 0.001}, {'alpha': 0.01}, {'alpha': 0.1}, {'alpha': 1.0}, {'alpha': 10.0}]
{'mean_fit_time': array([0.00070388, 0.00070631, 0.00062426, 0.00061269, 0.00061029]), 'std_fit_time': array([3.47088781e-04, 1.62248608e-04, 3.41188129e-05, 3.05416712e-05,
3.37911697e-05]), 'mean_score_time': array([0.00031955, 0.00033837, 0.00029499, 0.00029391, 0.00028908]), 'std_score_time': array([6.10654712e-05, 6.92493247e-05, 2.31523188e-05, 2.39786007e-05,
2.84609772e-05]), 'param_alpha': masked_array(data=[0.001, 0.01, 0.1, 1.0, 10.0],
mask=[False, False, False, False, False],
fill_value='?',
dtype=object), 'params': [{'alpha': 0.001}, {'alpha': 0.01}, {'alpha': 0.1}, {'alpha': 1.0}, {'alpha': 10.0}], 'split0_test_score': array([-10.67952536, -10.39488165, -10.65552463, -18.72750185,
-61.93179951]), 'split1_test_score': array([ -9.87220027, -10.41023081, -13.35114354, -25.60712323,
-73.69592853]), 'split2_test_score': array([-12.16441258, -12.53138129, -15.12499822, -26.0459513 ,
-71.47076539]), 'split3_test_score': array([ -5.61676338, -5.67773156, -6.66323739, -14.01557005,
-55.66946465]), 'split4_test_score': array([ -7.92153898, -8.26646109, -11.09340239, -22.8002393 ,
-71.90399695]), 'split5_test_score': array([ -9.19612781, -9.24462416, -10.41826717, -18.61993285,
-59.44727354]), 'split6_test_score': array([ -5.90964332, -6.14235726, -7.23455505, -15.49711113,
-64.93337459]), 'split7_test_score': array([-11.13889372, -11.45730033, -14.24627726, -28.18313944,
-85.1239582 ]), 'split8_test_score': array([ -5.74874147, -5.85090736, -6.83137373, -14.01267852,
-56.92542147]), 'split9_test_score': array([ -8.47682442, -8.31420673, -8.65467886, -17.11853485,
-66.17666028]), 'split10_test_score': array([ -9.35198079, -9.80690224, -12.387598 , -25.54617923,
-77.35148063]), 'split11_test_score': array([ -9.82916854, -10.10666708, -12.57045686, -24.56800419,
-75.70858794]), 'split12_test_score': array([ -6.47556094, -6.76946877, -8.70673972, -18.0331693 ,
-63.0402114 ]), 'split13_test_score': array([ -8.48428924, -8.70313059, -10.76058692, -20.07603885,
-62.93183747]), 'split14_test_score': array([-10.81949712, -10.66584226, -11.73844516, -19.77225839,
-64.00230604]), 'split15_test_score': array([ -7.38854163, -7.25004917, -7.62286105, -17.86956183,
-71.53042676]), 'split16_test_score': array([ -5.49654759, -5.56934031, -6.6454915 , -14.75883422,
-58.08812987]), 'split17_test_score': array([-10.69319848, -10.28578556, -9.89585888, -15.85933567,
-59.47153054]), 'split18_test_score': array([ -7.63374777, -8.04850684, -10.32483691, -19.59883203,
-63.26707251]), 'split19_test_score': array([-10.77707873, -11.15658773, -13.51411249, -24.42920864,
-71.22013234]), 'split20_test_score': array([ -6.47122683, -6.86863354, -8.87098322, -18.11494195,
-62.81407995]), 'split21_test_score': array([ -8.67477999, -8.38146022, -7.49844033, -10.6693015 ,
-43.31629941]), 'split22_test_score': array([ -8.20625209, -8.6877199 , -11.47777085, -25.45049361,
-86.70163771]), 'split23_test_score': array([ -9.63482564, -9.51397707, -10.39829211, -18.45028542,
-62.56488384]), 'split24_test_score': array([-11.75558465, -12.36743891, -15.42311389, -28.87781878,
-77.93734183]), 'split25_test_score': array([ -9.07618896, -9.41901178, -12.67545178, -25.62696388,
-77.45034836]), 'split26_test_score': array([ -7.89737091, -7.60225679, -8.12189709, -16.59244824,
-65.08786793]), 'split27_test_score': array([ -6.51288442, -6.14344237, -5.70976234, -13.03993054,
-59.79649215]), 'split28_test_score': array([-10.81229955, -11.19820017, -13.77234731, -24.5295236 ,
-68.78947041]), 'split29_test_score': array([ -8.72148939, -9.02157057, -11.07363878, -19.98035639,
-63.32265183]), 'split30_test_score': array([ -8.28909298, -9.06369062, -13.0913028 , -25.82384799,
-72.9991712 ]), 'split31_test_score': array([ -9.78140568, -9.58909843, -9.8810083 , -14.96460412,
-45.01216669]), 'split32_test_score': array([ -6.69546887, -6.81551844, -8.47771927, -19.802492 ,
-69.05940008]), 'split33_test_score': array([-10.41539055, -10.56379039, -12.0590966 , -20.65210873,
-62.75309742]), 'split34_test_score': array([ -8.44181243, -8.72497147, -11.05329391, -19.28678048,
-62.25575999]), 'split35_test_score': array([-10.59494674, -10.33748053, -10.91886831, -19.20162274,
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