Classification using Decision Trees | Data Science Dojo

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#1

Data Scientists use machine learning techniques to make predictions under a variety of scenarios. Machine learning can be used to predict whether a borrower will default on his mortgage or not, or what might be the median house value in a given zip code area. Depending upon whether the prediction is being made for a quantitative variable or a qualitative variable, a predictive model can be categorized as regression model (e.g. predicting median house values) or classification (e.g. predicting loan defaults) model.

This is a companion discussion topic for the original entry at https://blog.datasciencedojo.com/classification-decision-trees/
#2

Great article! You did an amazing job explaining the trees.

#3

It was indeed very well written.

Thank you.

#4
#5

Its a really good article.
I want to add, that for evaluation metrics use metric library. It will save you from doing things manually like classification errors, precision, recall and accuracy etc.

#6

Can you please clarify me about the data set, I am bit confused