Third attempt at the Kaggle competition "San Francisco Crime Classification"
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MultinomialModel-SFCrime.R
README.md

README.md

San Francisco Crime Classification (Kaggle) using R and multinomial logistic regression via neural networks

Overview

The "San Francisco Crime Classification" challenge, is a Kaggle competition aimed to predict the category of the crimes that occurred in the city, given the time and location of the incident.

In this post, I explain and outline my third solution to this challenge. This time using R.

Link to the competition: San Francisco Crime Classification

Learning method

The algorithm chosen for the implemented solution, is a variation of multinomial logistic regression, a classification model based on regression where the dependent variable (what we want to predict) is categorical (opposite of continuous), implemented using neural networks.

Report

A written report is available at San Francisco Crime Classification (Kaggle competition) using R and multinomial logistic regression via neural networks