How can I predict the outcome in python?

Question

I have the following code, where i predict a value from 4 input values:

import numpy as np
from sklearn.naive_bayes import GaussianNB
from sklearn.model_selection import train_test_split
from sklearn.neural_network import MLPClassifier

data = np.loadtxt('C:/Users/hedeg/Desktop/RulaSoftEdgePrediction.txt')

X_train = np.array(data[0:3500,0:4])
y_train = np.array(data[0:3500,4])


X_test = np.array(data[3500::,0:4])
y_test = np.array(data[3500::,4])

clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)
clf.fit(X_train, y_train)

I get this error msg:

raise ValueError("Unknown label type: %s" % repr(ys))
ValueError: Unknown label type: (array([1. , 1.1, 1.2, ..., 3. , 3. , 3. ]),)

How can i solve this problem?

Answer 1

Try to use this one:

from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_blobs
# generate 2d classification dataset
X, y = make_blobs(n_samples=100, centers=2, n_features=2, random_state=1)
# fit final model
model = LogisticRegression()
model.fit(X, y)

# example of training a final classification model
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_blobs
# generate 2d classification dataset
X, y = make_blobs(n_samples=100, centers=2, n_features=2, random_state=1)
# fit final model
model = LogisticRegression()
model.fit(X, y)