Question: solve it asap Q1: Consider the data set mentioned in link and apply k-mean clustering, considering the following conditions. 1. Map all the non integer

solve it asap
Q1: Consider the data set mentioned in link and apply k-mean clustering, considering the following conditions. 1. Map all the non integer columns to the integer values. 2. Apply pre-processing to clean data set. 3. Find optimal number of clusters. 4. Plot the clusters using scattered plot using different colors. 5. Pick 80 random values from data set and predict cluster. 6. Explain working of your code with the help of flow chart. Follow the link for data set https://pern-my.sharepoint.com/:x:/g/personal/awais cuiwah edu pk/ EVICTVMigFCSUNBcDMjV3gBbBE9R9;H-VCD5OBUeXtMOA?e=C4hmFB Q2: Consider the following data set "heart Disease" and apply decision tree. 1. Read the data set and train decision tree. 2. Apply decision tree to predict. 3. Use 70% dataset to train decision tree and 30% dataset to predict. 4. Plot tree using plot_tree. 5. Plot graph using graphviz displaying all the decisions. 6. Explain working of your code with the help of flow chart Follow the link for data set https://pern-my.sharepoint.com/:x:/g/personal/awais_cuiwah_edu_pk/ ERXvdCRTVshlivy95E35hZAB80yU8jHL_HZJqLgHltunaQ?e=zA1Acz Q1: Consider the data set mentioned in link and apply k-mean clustering, considering the following conditions. 1. Map all the non integer columns to the integer values. 2. Apply pre-processing to clean data set. 3. Find optimal number of clusters. 4. Plot the clusters using scattered plot using different colors. 5. Pick 80 random values from data set and predict cluster. 6. Explain working of your code with the help of flow chart. Follow the link for data set https://pern-my.sharepoint.com/:x:/g/personal/awais cuiwah edu pk/ EVICTVMigFCSUNBcDMjV3gBbBE9R9;H-VCD5OBUeXtMOA?e=C4hmFB Q2: Consider the following data set "heart Disease" and apply decision tree. 1. Read the data set and train decision tree. 2. Apply decision tree to predict. 3. Use 70% dataset to train decision tree and 30% dataset to predict. 4. Plot tree using plot_tree. 5. Plot graph using graphviz displaying all the decisions. 6. Explain working of your code with the help of flow chart Follow the link for data set https://pern-my.sharepoint.com/:x:/g/personal/awais_cuiwah_edu_pk/ ERXvdCRTVshlivy95E35hZAB80yU8jHL_HZJqLgHltunaQ?e=zA1Acz
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