Saving Model, Loading Model and Making Predictions for Linear Regression (in Weka)

1: Weka Explorer. Preprocess Tab.

2: Weka Explorer. Classify Tab.

3: Weka Explorer. Visualize Tab

4: Weka Experiment. Setup Tab. Advanced Configuration.

5: Weka Experiment Environment. Analyze Tab

6: Weka Experiment Environment. Comparing ZeroR with Linear Regression.

7: Saving and Loading models from SimpleCLI (documentation)

8: Use of TAB key in Weka SimpleCLI (Doc)

9: Use of Tab key in Weka SimpleCLI (Demo)

10: Training and Saving Linear Regression model from SimpleCLI.

Weka by default, picks up the last column as the target. So, Weka on reading from our file considered 'Day Count' as dependent variable and 'Close Price' as independent variable for 'COALINDIA' ticker data.

11: Dataset Corrected For Column Ordering

12: Training and Saving Linear Regression model after Correction in Dataset

13: Error during prediction for having only one col instead of two

14: Correction in test.csv

15: Error during prediction (string is not numeric)

16: Load Previously Saved Model in The Weka Explorer: Classify Tab

17: Select test data and select output predictions format

18: Select our previously saved model

19: View our saved model (Linear Regression) configuration

20: Re-evaluate model on current test set

21: View Classifier Output with saved model and extrapolated test data

Tags: Technology,Machine Learning,FOSS