In this program, we will take a look at the Allstate Kaggle competition. The script explores the data, models an xgboost model and tunes the parameters. There are two scripts included in this a python and an R script.

This competition can be found at the following link https://www.kaggle.com/c/allstate-claims-severity

What things you need to install the software and how to install them

###Python

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import OneHotEncoder
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor```

###R

library(readr)
library(rpart)
library(lattice)
library(Matrix)
library(xgboost)
library(readr)
library(stringr)
library(caret)
library(car)
library(PCAmixdata)
library(hydroGOF)
library(reshape)
library(onehot)
library(dplyr)

Both scripts essentially accomplish the same thing. They go through and explore the data the model and tune the paramters. The Python script takes a bit more data manipulation inorder to label and one hot encode the categorical variables.

Python @Ned Hulseman

R @James Noe @Ned Hulseman