I need to use Logistic Regression classifier I have dataset the length of each column 2000 this is all my code:
from statistics import mode
import pandas as pd
from sklearn.model_selection import KFold
from sklearn.metrics import plot_confusion_matrix
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import cross_val_predict
from sklearn.linear_model import LogisticRegression
# Importing the datasets
###Social_Network_Ads
datasets = pd.read_csv('C:/Users/n3.csv',header=None)
X = datasets.iloc[:, 0:5].values
Y = datasets.iloc[:, 5].values
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
X_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size = 0.25, random_state = 0)
# instantiate the model (using the default parameters)
model = LogisticRegression()
# fit the model with data
model.fit(X_Train, Y_Train)
predicted = cross_val_predict(mode, X_Train, Y_Train, cv=5)
train_acc = model.score(X_Train, Y_Train)
print("The Accuracy for Training Set is {}".format(train_acc*100))
But in I got on this error:
TypeError: Cannot clone object '<function mode at 0x000000FD6579B9D0>' (type <class 'function'>): it does not seem to be a scikit-learn estimator as it does not implement a 'get_params' method.
How solve this?
CodePudding user response:
Change this line
predicted = cross_val_predict(mode, X_Train, Y_Train, cv=5)
to
predicted = cross_val_predict(model, X_Train, Y_Train, cv=5)
You have a simple typo. You want to pass your estimator to the function but instead you passed mode
which is imported from statistics
. That's why the error tells you that it can not clone an object of type function. You are passing a function but it expects an estimator.