Sentimental analysis using svm(support vector machine)
Sentiment analysis for a dataset of comments which are classified as positive or negative using support vector machine. The steps included are data preprocessing and cleaning , label encoder, featur extraction using TF-IDF and then training and testing of model using svm.Image of the dataset used is
1.Loading the csv file to a pandas Dataframe. 2.Performing Data cleaning such as tokenization ,removing stopwards and unique characters. 3.Label encoding the sentiemnts for better classification. 4.Feature extraction done on the dataset. Tf-idf is used to find the weightage of the importance of words. 5. Performing SVM algorithm using scikit learn library and finding accuracy.
