Issue
I am a beginner in this field and was trying to model the data set as per logistic regression. The code is as follows:
import numpy as np
from matplotlib import pyplot as plt
import pandas as pnd
from sklearn.preprocessing import Imputer, LabelEncoder, OneHotEncoder, StandardScaler
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import confusion_matrix
# Import the dataset
data_set = pnd.read_csv("/Users/Siddharth/PycharmProjects/Deep_Learning/Classification Template/Social_Network_Ads.csv")
X = data_set.iloc[:, [2,3]].values
Y = data_set.iloc[:, 4].values
# Splitting the set into training set and testing set
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.25, random_state=0)
# Scaling the variables
scaler_x = StandardScaler()
x_train = scaler_x.fit_transform(x_train)
x_train = scaler_x.transform(x_test)
# Fitting Linear Regression to training data
classifier = LogisticRegression(random_state=0)
classifier.fit(x_train, y_train)
# Predicting the test set results
y_prediction = classifier.predict(x_test)
# Making the confusion matrix
conMat = confusion_matrix(y_true=y_test, y_pred=y_prediction)
print(conMat)
The error I am getting is in the classifier.fit(x_train, y_train)
.
The error is:
Traceback (most recent call last):
File "/Users/Siddharth/PycharmProjects/Deep_Learning/Logistic_regression.py", line 24, in <module>
classifier.fit(x_train, y_train)
File "/usr/local/lib/python3.6/site-packages/sklearn/linear_model/logistic.py", line 1173, in fit
order="C")
File "/usr/local/lib/python3.6/site-packages/sklearn/utils/validation.py", line 531, in check_X_y
check_consistent_length(X, y)
File "/usr/local/lib/python3.6/site-packages/sklearn/utils/validation.py", line 181, in check_consistent_length
" samples: %r" % [int(l) for l in lengths])
ValueError: Found input variables with inconsistent numbers of samples: [100, 300]
I have no clue why this is happening. Any help will be appreciated. Thank You!!
Solution
Seems like you have a typo here. You might want:
x_test = scaler_x.transform(x_test)
rather than: x_train = scaler_x.transform(x_test)
. In short, the error basically says sizes of your x_train
(which is actually x_test
) and y_train
doesn't match.
Answered By - Y. Luo
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