X_train_features = np.column_stack((X_train_features_1_ltr_landscapes,X_train_features_1_rtl_landscapes,X_train_features_1_ttb_landscapes,X_train_features_1_btt_landscapes,X_train_features_0_ltr_landscapes,X_train_features_0_rtl_landscapes,X_train_features_0_btt_landscapes,X_train_features_0_ttb_landscapes))
X_test_features = np.column_stack((X_test_features_1_ltr_landscapes,X_test_features_1_rtl_landscapes,X_test_features_1_ttb_landscapes,X_test_features_1_btt_landscapes,X_test_features_0_ltr_landscapes,X_test_features_0_rtl_landscapes,X_test_features_0_btt_landscapes,X_test_features_0_ttb_landscapes))
ridge_model = RidgeClassifier().fit(X_train_features, y_train)
landscapes_train_accuracy_ridge[t] = ridge_model.score(X_train_features, y_train)
landscapes_test_accuracy_ridge[t] = ridge_model.score(X_test_features, y_test)
c = 20
svm_model = SVC(kernel='rbf', C=c).fit(X_train_features, y_train)
landscapes_train_accuracy_svm[t] = svm_model.score(X_train_features, y_train)
landscapes_test_accuracy_svm[t] = svm_model.score(X_test_features, y_test)
### Carlson Coordinates
c = 50
X_train_features_0_ltr_cc1, X_train_features_0_ltr_cc2, X_train_features_0_ltr_cc3, X_train_features_0_ltr_cc4, X_test_features_0_ltr_cc1, X_test_features_0_ltr_cc2, X_test_features_0_ltr_cc3, X_test_features_0_ltr_cc4 = carlsson_coordinates(zero_dim_ltr_train, zero_dim_ltr_test)
X_train_features_1_ltr_cc1, X_train_features_1_ltr_cc2, X_train_features_1_ltr_cc3, X_train_features_1_ltr_cc4, X_test_features_1_ltr_cc1, X_test_features_1_ltr_cc2, X_test_features_1_ltr_cc3, X_test_features_1_ltr_cc4 = carlsson_coordinates(one_dim_ltr_train, one_dim_ltr_test)
X_train_features_0_rtl_cc1, X_train_features_0_rtl_cc2, X_train_features_0_rtl_cc3, X_train_features_0_rtl_cc4, X_test_features_0_rtl_cc1, X_test_features_0_rtl_cc2, X_test_features_0_rtl_cc3, X_test_features_0_rtl_cc4 = carlsson_coordinates(zero_dim_rtl_train, zero_dim_rtl_test)
X_train_features_1_rtl_cc1, X_train_features_1_rtl_cc2, X_train_features_1_rtl_cc3, X_train_features_1_rtl_cc4, X_test_features_1_rtl_cc1, X_test_features_1_rtl_cc2, X_test_features_1_rtl_cc3, X_test_features_1_rtl_cc4 = carlsson_coordinates(one_dim_rtl_train, one_dim_rtl_test)
X_train_features_0_btt_cc1, X_train_features_0_btt_cc2, X_train_features_0_btt_cc3, X_train_features_0_btt_cc4, X_test_features_0_btt_cc1, X_test_features_0_btt_cc2, X_test_features_0_btt_cc3, X_test_features_0_btt_cc4 = carlsson_coordinates(zero_dim_btt_train, zero_dim_btt_test)
X_train_features_1_btt_cc1, X_train_features_1_btt_cc2, X_train_features_1_btt_cc3, X_train_features_1_btt_cc4, X_test_features_1_btt_cc1, X_test_features_1_btt_cc2, X_test_features_1_btt_cc3, X_test_features_1_btt_cc4 = carlsson_coordinates(one_dim_btt_train, one_dim_btt_test)
X_train_features_0_ttb_cc1, X_train_features_0_ttb_cc2, X_train_features_0_ttb_cc3, X_train_features_0_ttb_cc4, X_test_features_0_ttb_cc1, X_test_features_0_ttb_cc2, X_test_features_0_ttb_cc3, X_test_features_0_ttb_cc4 = carlsson_coordinates(zero_dim_ttb_train, zero_dim_ttb_test)
X_train_features_1_ttb_cc1, X_train_features_1_ttb_cc2, X_train_features_1_ttb_cc3, X_train_features_1_ttb_cc4, X_test_features_1_ttb_cc1, X_test_features_1_ttb_cc2, X_test_features_1_ttb_cc3, X_test_features_1_ttb_cc4 = carlsson_coordinates(one_dim_ttb_train, one_dim_ttb_test)
X_train_features = np.column_stack((scale(X_train_features_0_ltr_cc1), scale(X_train_features_0_ltr_cc2),scale(X_train_features_0_ltr_cc3),scale(X_train_features_0_ltr_cc4),
scale(X_train_features_0_rtl_cc1), scale(X_train_features_0_rtl_cc2),scale(X_train_features_0_rtl_cc3),scale(X_train_features_0_rtl_cc4),
scale(X_train_features_0_ttb_cc1), scale(X_train_features_0_ttb_cc2),scale(X_train_features_0_ttb_cc3),scale(X_train_features_0_ttb_cc4),
scale(X_train_features_0_btt_cc1), scale(X_train_features_0_btt_cc2),scale(X_train_features_0_btt_cc3),scale(X_train_features_0_btt_cc4),
scale(X_train_features_1_ltr_cc1), scale(X_train_features_1_ltr_cc2),scale(X_train_features_1_ltr_cc3),scale(X_train_features_1_ltr_cc4),
scale(X_train_features_1_rtl_cc1), scale(X_train_features_1_rtl_cc2),scale(X_train_features_1_rtl_cc3),scale(X_train_features_1_rtl_cc4),
scale(X_train_features_1_ttb_cc1), scale(X_train_features_1_ttb_cc2),scale(X_train_features_1_ttb_cc3),scale(X_train_features_1_ttb_cc4),
X_test_features_S1_landscapes, X_test_features_S0_landscapes,
X_test_features_V1_landscapes, X_test_features_V0_landscapes))
ridge_model = RidgeClassifier().fit(X_train_features, y_train)
landscapes_train_accuracy_ridge[k] = ridge_model.score(
X_train_features, y_train)
landscapes_test_accuracy_ridge[k] = ridge_model.score(
X_test_features, y_test)
svm_model = SVC(kernel='rbf', C=1).fit(X_train_features, y_train)
landscapes_train_accuracy_svm[k] = svm_model.score(X_train_features,
y_train)
landscapes_test_accuracy_svm[k] = svm_model.score(X_test_features, y_test)
### Carlsson Coordinates
R0_train_features1_cc1, R0_train_features1_cc2, R0_train_features1_cc3, R0_train_features1_cc4, R0_test_features1_cc1, R0_test_features1_cc2, R0_test_features1_cc3, R0_test_features1_cc4 = carlsson_coordinates(
R0_train_sample, R0_test_sample)
G0_train_features1_cc1, G0_train_features1_cc2, G0_train_features1_cc3, G0_train_features1_cc4, G0_test_features1_cc1, G0_test_features1_cc2, G0_test_features1_cc3, G0_test_features1_cc4 = carlsson_coordinates(
G0_train_sample, G0_test_sample)
B0_train_features1_cc1, B0_train_features1_cc2, B0_train_features1_cc3, B0_train_features1_cc4, B0_test_features1_cc1, B0_test_features1_cc2, B0_test_features1_cc3, B0_test_features1_cc4 = carlsson_coordinates(
B0_train_sample, B0_test_sample)
X0_train_features1_cc1, X0_train_features1_cc2, X0_train_features1_cc3, X0_train_features1_cc4, X0_test_features1_cc1, X0_test_features1_cc2, X0_test_features1_cc3, X0_test_features1_cc4 = carlsson_coordinates(
X0_train_sample, X0_test_sample)
Y0_train_features1_cc1, Y0_train_features1_cc2, Y0_train_features1_cc3, Y0_train_features1_cc4, Y0_test_features1_cc1, Y0_test_features1_cc2, Y0_test_features1_cc3, Y0_test_features1_cc4 = carlsson_coordinates(
Y0_train_sample, Y0_test_sample)
Z0_train_features1_cc1, Z0_train_features1_cc2, Z0_train_features1_cc3, Z0_train_features1_cc4, Z0_test_features1_cc1, Z0_test_features1_cc2, Z0_test_features1_cc3, Z0_test_features1_cc4 = carlsson_coordinates(
Z0_train_sample, Z0_test_sample)
H0_train_features1_cc1, H0_train_features1_cc2, H0_train_features1_cc3, H0_train_features1_cc4, H0_test_features1_cc1, H0_test_features1_cc2, H0_test_features1_cc3, H0_test_features1_cc4 = carlsson_coordinates(
H0_train_sample, H0_test_sample)
S0_train_features1_cc1, S0_train_features1_cc2, S0_train_features1_cc3, S0_train_features1_cc4, S0_test_features1_cc1, S0_test_features1_cc2, S0_test_features1_cc3, S0_test_features1_cc4 = carlsson_coordinates(
S0_train_sample, S0_test_sample)
V0_train_features1_cc1, V0_train_features1_cc2, V0_train_features1_cc3, V0_train_features1_cc4, V0_test_features1_cc1, V0_test_features1_cc2, V0_test_features1_cc3, V0_test_features1_cc4 = carlsson_coordinates(
ridge_model = RidgeClassifier().fit(X_train_features, y_train)
landscapes_train_accuracy_ridge[k] = ridge_model.score(
X_train_features, y_train)
landscapes_test_accuracy_ridge[k] = ridge_model.score(
X_test_features, y_test)
c = 1
svm_model = SVC(kernel='rbf', C=c).fit(X_train_features, y_train)
landscapes_train_accuracy_svm[k] = svm_model.score(X_train_features,
y_train)
landscapes_test_accuracy_svm[k] = svm_model.score(X_test_features, y_test)
### Carlson Coordinates
c = 1
X_train_features1_cc1, X_train_features1_cc2, X_train_features1_cc3, X_train_features1_cc4, X_test_features1_cc1, X_test_features1_cc2, X_test_features1_cc3, X_test_features1_cc4 = carlsson_coordinates(
X_dgm1_train, X_dgm1_test)
X_train_features0_cc1, X_train_features0_cc2, X_train_features0_cc3, X_train_features0_cc4, X_test_features0_cc1, X_test_features0_cc2, X_test_features0_cc3, X_test_features0_cc4 = carlsson_coordinates(
X_dgm0_train, X_dgm0_test)
X_train_features = np.column_stack(
(X_train_features1_cc1, X_train_features1_cc2, X_train_features1_cc3,
X_train_features1_cc4, X_train_features0_cc1, X_train_features0_cc2,
X_train_features0_cc3, X_train_features0_cc4))
X_test_features = np.column_stack(
(X_test_features1_cc1, X_test_features1_cc2, X_test_features1_cc3,
X_test_features1_cc4, X_test_features0_cc1, X_test_features0_cc2,
X_test_features0_cc3, X_test_features0_cc4))
ridge_model = RidgeClassifier().fit(X_train_features, y_train)
carlson_train_accuracy_ridge[k] = ridge_model.score(
X_train_features, y_train)
carlson_test_accuracy_ridge[k] = ridge_model.score(X_test_features, y_test)