i need a help on python

Anonymous
timer Asked: Apr 23rd, 2017

Question description

Datasets

athletesTrainingSet.txt

athletesTestSet.txt

irisTrainingSet.data

irisTestSet.data

mpgTrainingSet.txt

mpgTestSet.txt

Buy using the above datasets calculate and compare the accuracy between KNN Accuracy and 10-fold Cross-validation with Logistic Regression.

Solve the following cases before calculating the accuracy.

  1. Import the sklearn library for all the datasets.
  2. Read the data for all the datasets and normalize them.
  3. For the athletes dataset replace the data of column Sport with 0, 1 and 2 accordingly. (For example 0 for Gymnastics, 1 for Basketball and 2 for Track). For the Iris dataset replace the data of column Species with 0, 1 and 2 accordingly. (For example 0 for Iris-setosa, 1 for Iris-versicolor and 2 for Iris-virginica). For the mpg dataset replace the data of column Model with 0,1, 2 and so on accordingly.(For example 0 for chevrolet chevelle malibu, 1 for buick skylark 320 and so on).
  4. Define the predictions and print them for all datasets.
  5. Create a classifier to search for an optimal value of K for KNN Algorithm for cross-validation accuracy.
  6. Plot the value of K for KNN Versus the cross-validation accuracy.
  7. Print out the KNN accuracy and 10-fold cross-validation with logistic regression and compare them.

All of the functions that you need for this system are given inside the notebook Cross-validation.ipynb in Module 10 of your class sessions.

You will need to test how accurate your classification system is by running your model on the test sets ( Explanation in detail is given in the Zacharski Chapter4)

You should submit / upload one IPython Notebook file ( .ipynb )

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