支持向量机算法 机器学习
为啥出现sklearn\svm_libsvm.pyx in sklearn.svm._libsvm.fit()
ValueError: C <= 0
部分代码
for i in range(720):
X_train,y_train, X_test, y_test = get_data_at_row_col(df1, str(i))
c = df2['C'][i]
g = df2['Gamma'][i]
yhat = prediction(X_train, y_train, c, g, np.array(X_test))
all_pred_GSV.append(list(yhat))
all_y_test.append(list(y_test))
def best_parameters(X,y,X_test,y_test): #training and get best parameters for models at each pixel
C = [1,10,100, 1e3,3e3]
gamma = [0.003,0.01,0.03,0.1,0.3,1]
best_gamma = 0
max_rs = -100
for c in C:
for g in gamma:
svr_rbf = SVR(kernel='rbf', C=c, gamma=g)
svr_rbf.fit(np.array(X), y)
yhat = svr_rbf.predict(np.array(X_test))
rs = r2_score(yhat,y_test)
if rs > max_rs and rs <1:
max_rs =rs
best_C = c
best_gamma = g
return best_C,best_gamma, max_rs