Hi guys,
I'm facing a problem when I am using decision_function in svm classifier. I
have *2 classes*, but decision function is returning an array with *one
column* only. Decision_function is working fine with iris dataset. I'm
afraid if I am doing something wrong while reading my files/data.
Any suggestions where might be the problem?
thanks!
P.S.: Please find here a chunk of the code:
I'm reading my tab-delimited files as:
data_cols = [2, 3, 4, 5, 6]
X_train = np.loadtxt(data_file, usecols=data_cols, delimiter = "\t")
y_train = np.genfromtxt(data_file, usecols = label_col, delimiter = "\t")
X_test = np.loadtxt(test_file, usecols=data_cols, delimiter = "\t")
y_test = np.genfromtxt(test_file, usecols = label_col, delimiter = "\t")
*Although it converts all the values in scientific format while reading the
files*
And I am calling decision functions as:
rbf_svc = svm.SVC(kernel='rbf',probability=True, C=C_val, gamma = g_val)
scores = rbf_svc.fit(X_train, y_train).score(X_test, y_test)
y_pred = rbf_svc.predict(X_test)
#y_score = rbf_svc.predict_proba(X_test)
y_score = rbf_svc.decision_function(X_test)
predict_proba gave array with 2 columns but decision_function returned an
array with one column only.
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