Quantify the dataset into probabilities and then classify it using the SVM implementation in scikit-learn. You are allowed to use any of the scikit functions.
You will use the Glass dataset from the UCI Machine learning repository (https://archive.ics.uci.edu/ml/datasets/glass+identification (Links to an external site.)). The dataset consists of 214 training instances of different types of glasses.
Please remember to provide text answers to the questions using text cells in the Colab notebook as well as writing the code.
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Hi, I have +5 experience dealing with machine learning algorithms and worked on multiple projects in this field, Please contact me to discuss more. Have a nice day
Hi , I am persue engineering in the Machine learning So I can do this task easily before this also I did more classification problems by using SVM and Logistic Regression.