# Load Validation Data and Labels
X_val = list(np.load('big_x_val.npy'))
Y_val = list(np.load('big_y_val.npy'))
# Project Data to 200 Dimensions using CCA
feat_dim = max(X[0].shape)
projections = Projections(feat_dim,CLASS_LABELS)
models = {} # Dictionary of key: model names, value: model instance
#########MODELS TO EVALUATE############
qda_m = QDA_Model(CLASS_LABELS)
models['qda'] = Model(qda_m)
lda_m = LDA_Model(CLASS_LABELS)
models['lda'] = Model(lda_m)
ridge_m = Ridge_Model(CLASS_LABELS)
models['ridge'] = Model(ridge_m)
ridge_m_10 = Ridge_Model(CLASS_LABELS)
ridge_m.lmbda = 10.0
models['ridge_lmda_10'] = Model(ridge_m_10)
ridge_m_01 = Ridge_Model(CLASS_LABELS)
ridge_m.lmbda = 0.1
models['ridge_lmda_01'] = Model(ridge_m_01)
def lclass():
# Load Training Data and Labels
X = list(np.load('little_x_train.npy'))
Y = list(np.load('little_y_train.npy'))
# Load Validation Data and Labels
X_val = list(np.load('little_x_val.npy'))
Y_val = list(np.load('little_y_val.npy'))
CLASS_LABELS = ['apple', 'banana', 'eggplant']
# Project Data to 200 Dimensions using CCA
feat_dim = max(X[0].shape)
projections = Projections(feat_dim, CLASS_LABELS)
cca_proj, white_cov = projections.cca_projection(X, Y, k=2)
X = projections.project(cca_proj, white_cov, X)
X_val = projections.project(cca_proj, white_cov, X_val)
####RUN RIDGE REGRESSION#####
ridge_m = Ridge_Model(CLASS_LABELS)
model = Model(ridge_m)
model.train_model(X, Y)
model.test_model(X, Y)
model.test_model(X_val, Y_val)
####RUN LDA REGRESSION#####
lda_m = LDA_Model(CLASS_LABELS)
model = Model(lda_m)
model.train_model(X, Y)
model.test_model(X, Y)
model.test_model(X_val, Y_val)
####RUN QDA REGRESSION#####
qda_m = QDA_Model(CLASS_LABELS)
model = Model(qda_m)
model.train_model(X, Y)
model.test_model(X, Y)
model.test_model(X_val, Y_val)
####RUN SVM REGRESSION#####
svm_m = SVM_Model(CLASS_LABELS)
model = Model(svm_m)
model.train_model(X, Y)
model.test_model(X, Y)
model.test_model(X_val, Y_val)
####RUN Logistic REGRESSION#####
lr_m = Logistic_Model(CLASS_LABELS)
model = Model(lr_m)
model.train_model(X, Y)
model.test_model(X, Y)
model.test_model(X_val, Y_val)