I am trying to create one machine learning model using Kernel ridge regression with k-fold but I am getting the below error. Much appreciate for your informations-
datasetTrain = pd.read_csv('D:/set_AB.csv')
datasetTest = pd.read_csv('D:/set_C.csv')
X = datasetTrain
y = datasetTest
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
I am getting the following error----
ValueError: Found input variables with inconsistent numbers of samples: [140, 70]
enter code here
You are doing train_test_split that is fundamentally wrong.
Error: len(datasetTrain)=140, len(datasetTest)=70. Therefore dimension mismatch.
datasetTrain is the dataset used for training. The train dataset in your case should contain:
Xtrain: The input or the predictor variables that impact the target variable .
ytrain: The target variable.
datasetTest is the dataset used for test. The test dataset in your case should contain:
Xtest: The input or the predictor variables that impact the target variable.
ytest: The target variable.
Concatenate both the datasetTrain and datasetTest along dim=0.
final_df = pd.concat([datasetTrain, datasetTest])
X = final_df["only those columns which are input variables"]
y = final_df["target_variable"]
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
"""
Creation of model and the training code goes here
"""
