python - ValueError: bad input shape (560, 5) sklearn

Question

I am starting to write the learnig machine model. I have a Y_train dataset containing the labels, there are 5 classes. The X_train dataset contains the samples. I try to make my model with the help of a logistic regression. shape : X_train ((560, 20531)) and Y_train ((560, 5)) have the same dimensions. I have seen a few publications associated with the same problem but I have not been able to solve the problem. I don't know how to correct this error,can you help me please ?

X = pd.read_csv('/Users/lottie/desktop/data.csv', header=None, skiprows=[0])
Y = pd.read_csv('/Users/lottie/desktop/labels.csv', header=None)

Y_encoded = list()
for i in Y.loc[0:,1] :
    if i == 'BRCA' : Y_encoded.append(0)
    if i == 'KIRC' : Y_encoded.append(1)
    if i == 'COAD' : Y_encoded.append(2)
    if i == 'LUAD' : Y_encoded.append(3)
    if i == 'PRAD' : Y_encoded.append(4)
Y_bis = to_categorical(Y_encoded)


#separation of the data
X_train, X_test, Y_train, Y_test = train_test_split(X, Y_bis, test_size=0.30, random_state=42)

regression_log = linear_model.LogisticRegression(multi_class='multinomial', solver='newton-cg')

X_train=X_train.iloc[:,1:]

#train model
train_train = regression_log.fit(X_train, Y_train)

Answer 1

What exactly is your X_train exactly? It looks like at first glance that you're inverting your number of samples with your number of features.

Try X.shape and Y.shape and tell me what the console gives.