Classification Techniques Using Decision Tree & Random Forest

Classification algorithms in machine learning use input training data to predict the likelihood that subsequent data will fall into one of the predetermined categories.

One of the most common uses of classification is filtering emails into “spam” or “non-spam.” In short, classification is a form of “pattern recognition,” with classification algorithms applied to the training data to find the same pattern (similar words or sentiments, number sequences, etc.) in future sets of data. 

Using classification algorithms, which we’ll go into more detail about below, text analysis software can perform tasks like aspect-based sentiment analysis to categorize unstructured text by topic and polarity of opinion (positive, negative, neutral, and beyond).