# Week04 HW

Guidelines · Share awning attempt on your response  · Share the cipher and the plots  · Put your name and id number · Clear mark catechism number · Upload Word document · Insert Cover folio Questions Attempted HW04 Cover Sheet Identify all questions that you attempted in this template Q1 Chapter 04 Allocation Examples Part 1 Analysis logistic corruption in Chapter 4 - Classification https://github.com/JWarmenhoven/ISLR-python Use the examples to analysis 4.3 logistic corruption for the ISLR Text a. Plot Figure 4.1  b. Plot Figure 4.2 c. Table 4.1, 4.2, 4.3 d. Plot Figure 4.3 Hint use - https://nbviewer.jupyter.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%204.ipynb#4.3-Logistic-Regression Part 2 Application to Caravan Insurance Data¶ Use Caravan.csv to administer KNN and Logistic Corruption to the Caravan data Hint – use https://nbviewer.jupyter.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%204.ipynb#4.6.5-K-Nearest-Neighbors Q2. Allocation Textbook Examples Using the Boston abstracts set, fit allocation models in adjustment to adumbrate whether a accustomed suburb has a abomination amount aloft or beneath the median. Explore logistic regression, and KNN models application assorted subsets of the predictors. Describe your findings. Hint – use: https://botlnec.github.io/islp/sols/chapter4/exercise13/ Q3 Iris Abstracts Set and Allocation (iris.csv) The Iris dataset was acclimated in R.A. Fisher's archetypal 1936 paper. It includes three iris breed with 50 samples anniversary as able-bodied as some backdrop about anniversary flower. One annual breed is linearly adaptable from the alternative two, but the alternative two are not linearly adaptable from anniversary other. The columns in this dataset are: · Id · Sepal Length Cm · Sepal Width Cm · Petal Length Cm · Petal Width Cm · Species a. Plot the iris dataset – i) “Sepal Length vs Sepal Width” ii) “Petal Length vs Petal Width” Split into Training / Analysis and  b. Administer Naïve Bayes Classifier to allocate breed with the accommodation boundaries c. Administer logistic corruption to allocate breed with the accommodation boundaries d. Administer KNN algorithm to allocate breed with the accommodation boundaries e. Compare the “Truth matrix” and Accuracy of the three algorithms    TP TN FP FN Accuracy   Naïve Bayes   Logistic Regression   KNN Hint Naïve Bayes - https://xavierbourretsicotte.github.io/Naive_Bayes_Classifier.html Logistic Corruption –  https://scikit-learn.org/stable/auto_examples/linear_model/plot_iris_logistic.html https://www.datacamp.com/community/tutorials/understanding-logistic-regression-python KNN Algorithm –  https://www.ritchieng.com/machine-learning-k-nearest-neighbors-knn/ Q4 Titanic Abstracts Set and Allocation (titanic.zip – already afar as test, train) a. Perform Exploratory Abstracts Analysis b. Do Feature Engineering c. Administer logistic regression d. Administer KNN algorithm Hint https://www.kaggle.com/angps95/basic-classification-methods-for-titanic Q5. How does k-fold cantankerous validation and filigree chase on the Social Ads Network data Use the references the explain how the two assignment calm to appraise a model https://scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_digits.html https://sebastianraschka.com/faq/docs/evaluate-a-model.html

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