The error you're encountering, "ValueError: Found input variables with inconsistent numbers of samples: [365, 1093]," suggests that the dimensions of your training and testing data are not aligned correctly. It appears that the number of samples in your x_train and y_train sets does not match the number of samples in your x_test and y_test sets.
To resolve this issue, you should verify that the dimensions of your training and testing sets are consistent. Here are a few things to check:
Check Dimensions: Ensure that x_train and y_train have the same number of samples. Similarly, x_test and y_test should also have the same number of samples.
print("x_train shape:", x_train.shape)
print("y_train shape:", y_train.shape)
print("x_test shape:", x_test.shape)
print("y_test shape:", y_test.shape)
import numpy as np
# Assuming x_train, y_train, x_test, and y_test are your input variables
# Check dimensions of training data
print("Training data dimensions:")
print("x_train shape:", np.shape(x_train))
print("y_train shape:", np.shape(y_train))
# Check dimensions of testing data
print("\nTesting data dimensions:")
print("x_test shape:", np.shape(x_test))
print("y_test shape:", np.shape(y_test))
Data Cleaning: Make sure that your data cleaning and preprocessing steps are consistent between your training and testing sets. If you are performing any operations on the training set, ensure that the same operations are applied to the testing set.
Data Splitting: If you are manually splitting your data into training and testing sets, double-check the logic of your splitting procedure to ensure that it's not causing the inconsistency.
Check Data Loading: If you are loading data from external sources, verify that the loading process is correct and that the data is being loaded into the correct variables.
After making these checks, you should be able to identify the source of the inconsistency. Adjust your data preparation steps accordingly to ensure that both your training and testing sets have the same number of samples.
If the issue persists, you might want to share more details about how you are preparing and splitting your data, so I can provide more specific assistance.
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