Classification Algorithms Machine Learning and compare machine learning algorithms, As we know the Machine learning algorithm is divided into supervise and unsupervised learning. Classification algorithms is a part of supervised learning where we train the Machine learning model with labeled output data and test the model performance by comparing with existing test data. There are many classification algorithms present in the machine learning library, but for this article will use Logistic Regression, KNN, SVM, Decision tree, Random forest etc. python 3+ and compare the result. Classification output means where output is either True or False, Yes or No, Positive or negative or 0 or 1.
Now we need to convert categorical values to numerical values since the classification algorithm requires numerical value to fit and calculate the prediction, there are two popular way to achieve this either using one-hot encoder or get_dummies method, so we are using pd.get_dummies method for this conversion since it is simple and then drop last column to avoid dummy variable trap.
Classification Algorithms Machine Learning and compare machine learning algorithms work, we can further use parameter tuning to get good results.
-- Edited by onclick360 on Sunday 19th of January 2020 01:21:27 PM
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