1) Wine data is available in the appendix. Read the data into the system. 2) Show the size of the data, the statistical summary of the content, the distribution of the data according to the class variable, draw the box graph histogram and scatter plot matrix for the data, and explain it as a comment line on the code for each graph.
Computer Science
1) Wine data is available in the appendix. Read the data into the system.
2) Show the size of the data, the statistical summary of the content, the distribution of the data according to the class variable, draw the box graph histogram and scatter plot matrix for the data, and explain it as a comment line on the code for each graph.
3) Divide the data appropriately into training and test data. Apply the classification models (min 4) under the Sklearn library and generate the accuracy of the results and confusion matrix(Error Matrix). Explain what you understand from the error matrix as a comment line in the code.
4) Also, apply the models you applied in item 3 with cross-validation and note the results.
5) Compare item 3 and item four and write a comment on the code as a comment line.
Bonus: Try to get the highest accuracy by performing the data preprocessing steps.
Note: Develop the coding on the Python
Please help write the code.
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