Partha Chaudhuri
Active Member
Hello Friend;
This is a great video on Bayes theorem
hhttps://youtu.be/HZGCoVF3YvM
This is a great video on Bayes theorem
hhttps://youtu.be/HZGCoVF3YvM
Recommended. Know people from your network.
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Sign Upi created list of columns which has var is zeroerror in calculating variance equals to zero
i created list of columns which has var is zero
#Creating list out of the index above
column_to_delete =list(data.var()[data.var() == 0].index)
then I use drop function and in drop, I pass all lists of columns to delete.
ID is a column which will not go in model..You need to drop that from feature setI am facing some issue while calculating LogisticRegression and linearRegrassion using PCA
Please check and let me know where is the in my code...
Hi SHRILAVANYA H ADIGOPULA,In the project1-Mercedes greenary manufacturing, I found the accuracy for the train dataset as there is no dependent variable for test data how to find the accuracy of the test data?
please anyone help regarding the same
Thank you @Raghavendra B M sir for your valuable response.Hi SHRILAVANYA H ADIGOPULA,
Just download and go through the Project Mentoring recording for the project for the "Mercedes-Benz Greener Manufacturing" from the below link. The project is properly discussed in the recording :
# Project Name - Mercedes-Benz Greener Manufacturing - Project Mentoring :
Regards,
Raghavendra
this error might indicate that you are trying to train the Random Forest Classifier on a dataset that consists of 1459 samples and 1460 labels of your datset. And the number of testX != the number of y.ValueError Traceback (most recent call last)
<ipython-input-28-a85277fe1e0e> in <module>
----> 1 regressor.fit(x_train, y_train)
2 regressor.predict(x_test)
/opt/anaconda3/lib/python3.8/site-packages/sklearn/tree/_classes.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
1240 """
1241
-> 1242 super().fit(
1243 X, y,
1244 sample_weight=sample_weight,
/opt/anaconda3/lib/python3.8/site-packages/sklearn/tree/_classes.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
270
271 if len(y) != n_samples:
--> 272 raise ValueError("Number of labels=%d does not match "
273 "number of samples=%d" % (len(y), n_samples))
274 if not 0 <= self.min_weight_fraction_leaf <= 0.5:
ValueError: Number of labels=4 does not match number of samples=6
why I am receiving this error while executing the code ?
Thanks.