A Practical Guide to Machine Learning with Python/

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SVM Implementation Steps: 1 to 7

SVM Implementation Steps: 1 to 7

This lesson will cover the implementation steps (1-7) of support vector machines.

We'll cover the following...

1) Import libraries

You will be using SVC (Support Vector Classifier) from the Scikit-learn library to implement this model and evaluating the predictions using a classification report and confusion matrix. You will later optimize the model using grid search.

Python 3.5
#1- Import libraries
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
from sklearn.metrics import classification_report, confusion_matrix
from sklearn.model_selection import GridSearchCV

Note: Codes of further steps won’t ...