train_sizes=np.linspace(0.1, 1.0, 20))
fig_adult_lc.savefig(root_path + "/plots/decision_tree/adult_lc.png")
fig_flag_lc = gp.plot_learning_curve(dt_flag,
"flag learning curve",
flag_x,
flag_y,
cv=3,
train_sizes=np.linspace(0.1, 1.0, 20))
fig_flag_lc.savefig(root_path + "/plots/decision_tree/flag_lc.png")
print("########## Plotting Max Depth Validation Curves... ##########")
fig_adult_vc1 = gp.plot_validation_curve(dt_adult,
"Max Depth Adult Validation Curve",
adult_x,
adult_y,
param_name="max_depth",
param_range=np.linspace(1, 50, 25),
cv=5)
fig_adult_vc1.savefig(root_path +
"/plots/decision_tree/max_depth_adult_vc.png")
fig_flag_vc1 = gp.plot_validation_curve(dt_flag,
"Max Depth Flag Validation Curve",
flag_x,
flag_y,
param_name="max_depth",
param_range=np.linspace(1, 50, 25),
cv=5)
fig_flag_vc1.savefig(root_path + "/plots/decision_tree/max_depth_flag_vc.png")
train_sizes=np.linspace(0.1, 1.0, 7))
fig_adult_lc.savefig(root_path + "/plots/nn/adult_lc.png")
fig_flag_lc = gp.plot_learning_curve(nn_flag,
"Flag - learning curve",
flag_x.todense(),
flag_y.values.ravel(),
cv=3,
train_sizes=np.linspace(0.1, 1.0, 50))
fig_flag_lc.savefig(root_path + "/plots/nn/flag_lc.png")
print("########## Plotting alpha Validation Curves... ##########")
fig_adult_vc1 = gp.plot_validation_curve(nn_adult,
"Adult - alpha Validation Curve",
adult_x.todense(),
adult_y.values.ravel(),
param_name="alpha",
param_range=np.linspace(
0.01, 0.05, 5),
cv=3)
fig_adult_vc1.savefig(root_path + "/plots/nn/alpha_adult_vc.png")
fig_flag_vc1 = gp.plot_validation_curve(
nn_flag,
"Flag - alpha Validation Curve",
flag_x.todense(),
flag_y.values.ravel(),
param_name="alpha",
param_range=10.0**-np.arange(0.1, 7, 0.1),
cv=5)
fig_flag_vc1.savefig(root_path + "/plots/nn/alpha_flag_vc.png")
train_sizes=np.linspace(0.1, 1.0, 40))
fig_adult_lc.savefig(root_path + "/plots/boost/adult_lc.png")
fig_flag_lc = gp.plot_learning_curve(boost_flag,
"Flag - learning curve",
flag_x.todense(),
flag_y.values.ravel(),
cv=3,
train_sizes=np.linspace(0.1, 1.0, 40))
fig_flag_lc.savefig(root_path + "/plots/boost/flag_lc.png")
print("########## Plotting n_estimators Validation Curves... ##########")
fig_adult_vc1 = gp.plot_validation_curve(
boost_adult,
"Adult - n_estimators Validation Curve",
adult_x.todense(),
adult_y.values.ravel(),
param_name="n_estimators",
param_range=range(1, 100, 2),
cv=5)
fig_adult_vc1.savefig(root_path + "/plots/boost/n_estimators_adult_vc.png")
fig_flag_vc1 = gp.plot_validation_curve(boost_flag,
"Flag - n_estimators Validation Curve",
flag_x.todense(),
flag_y.values.ravel(),
param_name="n_estimators",
param_range=range(1, 100),
cv=5)
fig_flag_vc1.savefig(root_path + "/plots/boost/n_estimators_flag_vc.png")
print("########## Plotting learning_rate Validation Curves... ##########")
train_sizes=np.linspace(0.1, 1.0, 5))
fig_adult_lc2.savefig(root_path + "/plots/svm/rbf_adult_lc.png")
fig_flag_lc2 = gp.plot_learning_curve(svc_flag2,
"Flag - learning curve",
flag_x.todense(),
flag_y.values.ravel(),
cv=3,
train_sizes=np.linspace(0.1, 1.0, 10))
fig_flag_lc2.savefig(root_path + "/plots/svm/rbf_flag_lc.png")
print("########## Plotting C Validation Curves... ##########")
fig_adult_vc1 = gp.plot_validation_curve(svc_adult,
"Adult - C Validation Curve",
adult_x.todense(),
adult_y.values.ravel(),
param_name="C",
param_range=np.linspace(0.01, 4, 50),
cv=5)
fig_adult_vc1.savefig(root_path + "/plots/svm/C_adult_vc.png")
fig_flag_vc1 = gp.plot_validation_curve(svc_flag,
"Flag - C Validation Curve",
flag_x.todense(),
flag_y.values.ravel(),
param_name="C",
param_range=np.linspace(0.01, 0.5, 25),
cv=5)
fig_flag_vc1.savefig(root_path + "/plots/svm/C_flag_vc.png")
fig_adult_vc2 = gp.plot_validation_curve(svc_adult,
train_sizes=np.linspace(0.1, 1.0, 20))
fig_adult_lc.savefig(root_path + "/plots/knn/adult_lc.png")
fig_flag_lc = gp.plot_learning_curve(knn_flag,
"Flag - learning curve",
flag_x.todense(),
flag_y.values.ravel(),
cv=3,
train_sizes=np.linspace(0.1, 1.0, 20))
fig_flag_lc.savefig(root_path + "/plots/knn/flag_lc.png")
print("########## Plotting n_neighbors Validation Curves... ##########")
fig_adult_vc1 = gp.plot_validation_curve(
knn_adult,
"Adult - n_neighbors Validation Curve",
adult_x.todense(),
adult_y.values.ravel(),
param_name="n_neighbors",
param_range=range(1, 50),
cv=5)
fig_adult_vc1.savefig(root_path + "/plots/knn/n_neighbors2_adult_vc.png")
fig_flag_vc1 = gp.plot_validation_curve(knn_flag,
"Flag - n_neighbors Validation Curve",
flag_x.todense(),
flag_y.values.ravel(),
param_name="n_neighbors",
param_range=range(1, 50),
cv=5)
fig_flag_vc1.savefig(root_path + "/plots/knn/n_neighbors2_flag_vc.png")
print("########## Plotting Distance Metric Validation Curves... ##########")