Add missing tuning results (#66)

scikit-learn-contrib · Nov 30, 2022 · 221b39b · 221b39b
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diff --git a/benchmarks/consumer_complaints/results/flat/lightgbm/optimization_results.md b/benchmarks/consumer_complaints/results/flat/lightgbm/optimization_results.md
@@ -4,7 +4,9 @@
 |----------|------|-------|------------------|
 |{'num_leaves': 31, 'n_estimators': 100, 'min_child_samples': 20}|[0.469, 0.423, 0.195, 0.409, 0.29]|0.357|0.100|
 |{'num_leaves': 62, 'n_estimators': 100, 'min_child_samples': 40}|[0.225, 0.47, 0.313, 0.373, 0.299]|0.336|0.082|
+|{'num_leaves': 31, 'n_estimators': 100, 'min_child_samples': 40}|[0.248, 0.37, 0.459, 0.438, 0.476]|0.398|0.083|
 |{'num_leaves': 62, 'n_estimators': 200, 'min_child_samples': 40}|[0.453, 0.177, 0.455, 0.357, 0.135]|0.316|0.135|
+|{'num_leaves': 62, 'n_estimators': 200, 'min_child_samples': 20}|[0.403, 0.471, 0.158, 0.385, 0.376]|0.358|0.106|
 |{'num_leaves': 31, 'n_estimators': 200, 'min_child_samples': 40}|[0.338, 0.397, 0.46, 0.401, 0.444]|0.408|0.043|
 |{'num_leaves': 31, 'n_estimators': 200, 'min_child_samples': 20}|[0.296, 0.48, 0.2, 0.203, 0.244]|0.285|0.104|
 |{'num_leaves': 62, 'n_estimators': 100, 'min_child_samples': 20}|[0.463, 0.368, 0.477, 0.076, 0.452]|0.367|0.151|
diff --git a/benchmarks/consumer_complaints/results/flat/random_forest/optimization_results.md b/benchmarks/consumer_complaints/results/flat/random_forest/optimization_results.md
@@ -4,6 +4,7 @@
 |----------|------|-------|------------------|
 |{'n_estimators': 200, 'criterion': 'entropy'}|[0.617, 0.616, 0.618, 0.618, 0.614]|0.617|0.001|
 |{'n_estimators': 100, 'criterion': 'gini'}|[0.656, 0.655, 0.656, 0.656, 0.658]|0.656|0.001|
+|{'n_estimators': 100, 'criterion': 'entropy'}|[0.613, 0.613, 0.615, 0.616, 0.615]|0.614|0.001|
 |{'n_estimators': 100, 'criterion': 'log_loss'}|[0.615, 0.617, 0.619, 0.618, 0.617]|0.617|0.001|
 |{'n_estimators': 200, 'criterion': 'gini'}|[0.659, 0.658, 0.66, 0.66, 0.657]|0.659|0.001|
 |{'n_estimators': 200, 'criterion': 'log_loss'}|[0.618, 0.616, 0.619, 0.618, 0.616]|0.617|0.001|
diff --git a/..._complaints/results/local_classifier_per_level/lightgbm/optimization_results.md b/..._complaints/results/local_classifier_per_level/lightgbm/optimization_results.md
@@ -4,6 +4,7 @@
 |----------|------|-------|------------------|
 |{'num_leaves': 62, 'n_estimators': 100, 'min_child_samples': 20}|[0.676, 0.666, 0.66, 0.657, 0.661]|0.664|0.007|
 |{'num_leaves': 31, 'n_estimators': 200, 'min_child_samples': 40}|[0.661, 0.668, 0.643, 0.664, 0.658]|0.659|0.009|
+|{'num_leaves': 62, 'n_estimators': 100, 'min_child_samples': 40}|[0.66, 0.669, 0.676, 0.665, 0.664]|0.667|0.006|
 |{'num_leaves': 31, 'n_estimators': 200, 'min_child_samples': 20}|[0.649, 0.651, 0.66, 0.658, 0.655]|0.655|0.004|
 |{'num_leaves': 62, 'n_estimators': 200, 'min_child_samples': 40}|[0.651, 0.66, 0.668, 0.657, 0.654]|0.658|0.006|
 |{'num_leaves': 31, 'n_estimators': 100, 'min_child_samples': 40}|[0.675, 0.681, 0.652, 0.669, 0.672]|0.670|0.010|

diff --git a/...laints/results/local_classifier_per_level/random_forest/optimization_results.md b/...laints/results/local_classifier_per_level/random_forest/optimization_results.md
@@ -5,4 +5,6 @@
 |{'n_estimators': 100, 'criterion': 'log_loss'}|[0.713, 0.713, 0.715, 0.712, 0.715]|0.714|0.001|
 |{'n_estimators': 100, 'criterion': 'entropy'}|[0.714, 0.712, 0.716, 0.715, 0.714]|0.714|0.001|
 |{'n_estimators': 200, 'criterion': 'log_loss'}|[0.718, 0.718, 0.72, 0.72, 0.718]|0.719|0.001|
+|{'n_estimators': 100, 'criterion': 'gini'}|[0.724, 0.726, 0.726, 0.725, 0.724]|0.725|0.001|
 |{'n_estimators': 200, 'criterion': 'gini'}|[0.729, 0.73, 0.732, 0.73, 0.73]|0.730|0.001|
+|{'n_estimators': 200, 'criterion': 'entropy'}|[0.719, 0.72, 0.719, 0.72, 0.719]|0.720|0.001|
diff --git a/...r_complaints/results/local_classifier_per_node/lightgbm/optimization_results.md b/...r_complaints/results/local_classifier_per_node/lightgbm/optimization_results.md
@@ -4,5 +4,9 @@
 |----------|------|-------|------------------|
 |{'num_leaves': 62, 'n_estimators': 100, 'min_child_samples': 40}|[0.775, 0.778, 0.777, 0.777, 0.774]|0.776|0.001|
 |{'num_leaves': 62, 'n_estimators': 200, 'min_child_samples': 20}|[0.789, 0.789, 0.789, 0.784, 0.788]|0.788|0.002|
+|{'num_leaves': 31, 'n_estimators': 200, 'min_child_samples': 40}|[0.779, 0.781, 0.78, 0.78, 0.777]|0.779|0.001|
 |{'num_leaves': 31, 'n_estimators': 100, 'min_child_samples': 20}|[0.769, 0.771, 0.757, 0.77, 0.768]|0.767|0.005|
 |{'num_leaves': 31, 'n_estimators': 200, 'min_child_samples': 20}|[0.782, 0.783, 0.769, 0.781, 0.78]|0.779|0.005|
+|{'num_leaves': 31, 'n_estimators': 100, 'min_child_samples': 40}|[0.77, 0.772, 0.768, 0.771, 0.77]|0.770|0.001|
+|{'num_leaves': 62, 'n_estimators': 200, 'min_child_samples': 40}|[0.784, 0.786, 0.784, 0.784, 0.783]|0.784|0.001|
+|{'num_leaves': 62, 'n_estimators': 100, 'min_child_samples': 20}|[0.776, 0.778, 0.774, 0.776, 0.775]|0.776|0.001|
diff --git a/...aints/results/local_classifier_per_parent_node/lightgbm/optimization_results.md b/...aints/results/local_classifier_per_parent_node/lightgbm/optimization_results.md
@@ -8,4 +8,5 @@
 |{'num_leaves': 62, 'n_estimators': 100, 'min_child_samples': 40}|[0.741, 0.745, 0.748, 0.738, 0.738]|0.742|0.004|
 |{'num_leaves': 31, 'n_estimators': 100, 'min_child_samples': 20}|[0.72, 0.717, 0.726, 0.739, 0.724]|0.725|0.008|
 |{'num_leaves': 31, 'n_estimators': 200, 'min_child_samples': 20}|[0.725, 0.723, 0.732, 0.733, 0.722]|0.727|0.005|
+|{'num_leaves': 31, 'n_estimators': 100, 'min_child_samples': 40}|[0.748, 0.748, 0.73, 0.746, 0.746]|0.743|0.007|
 |{'num_leaves': 62, 'n_estimators': 200, 'min_child_samples': 20}|[0.735, 0.724, 0.726, 0.723, 0.721]|0.726|0.005|
diff --git a/...ts/local_classifier_per_parent_node/logistic_regression/optimization_results.md b/...ts/local_classifier_per_parent_node/logistic_regression/optimization_results.md
@@ -2,6 +2,7 @@
 ## Base classifier: logistic_regression
 |Parameters|Scores|Average|Standard deviation|
 |----------|------|-------|------------------|
+|{'solver': 'saga', 'max_iter': 10000}|[0.777, 0.779, 0.778, 0.779, 0.778]|0.778|0.001|
 |{'solver': 'liblinear', 'max_iter': 10000}|[0.774, 0.774, 0.774, 0.775, 0.774]|0.774|0.001|
 |{'solver': 'lbfgs', 'max_iter': 10000}|[0.777, 0.779, 0.778, 0.779, 0.778]|0.778|0.001|
 |{'solver': 'sag', 'max_iter': 10000}|[0.777, 0.779, 0.778, 0.779, 0.778]|0.778|0.001|

diff --git a/.../results/local_classifier_per_parent_node/random_forest/optimization_results.md b/.../results/local_classifier_per_parent_node/random_forest/optimization_results.md
@@ -2,7 +2,9 @@
 ## Base classifier: random_forest
 |Parameters|Scores|Average|Standard deviation|
 |----------|------|-------|------------------|
+|{'n_estimators': 100, 'criterion': 'gini'}|[0.727, 0.729, 0.729, 0.728, 0.729]|0.728|0.001|
 |{'n_estimators': 200, 'criterion': 'entropy'}|[0.72, 0.721, 0.723, 0.721, 0.722]|0.721|0.001|
+|{'n_estimators': 100, 'criterion': 'log_loss'}|[0.717, 0.719, 0.717, 0.717, 0.717]|0.717|0.001|
 |{'n_estimators': 200, 'criterion': 'gini'}|[0.733, 0.732, 0.733, 0.733, 0.732]|0.733|0.001|
 |{'n_estimators': 200, 'criterion': 'log_loss'}|[0.72, 0.722, 0.72, 0.721, 0.721]|0.721|0.001|
 |{'n_estimators': 100, 'criterion': 'entropy'}|[0.715, 0.716, 0.716, 0.717, 0.717]|0.716|0.001|