Hello everyone, Your term project is now available. We have chosen a project fro

Question

Hello everyone, Your term project is now available. We have chosen a project from www.kaggle.com as your term project. You can access exhaustive information from the link provided below. Your task is to classify the data which has 93 features and more than 200.000 products from Otto group. It is still possible to submit your result through website. In this project, you can use any kind of programming language(python, scala, matlab, java, R etc) and framework(scikit,mllib etc.) to build your model. Project: https://www.kaggle.eom/c/otto-group-product-classification-challenge/data (Of course you can copy the following code snippet from Kernel!) import pandas as pd train = pd.read csv("../input/train.csv")

Explanation / Answer

require(xgboost) require(methods) train = read.csv('../input/train.csv',header=TRUE,stringsAsFactors = F) test = read.csv('../input/test.csv',header=TRUE,stringsAsFactors = F) train = train[,-1] test = test[,-1] y = train[,ncol(train)] y = gsub('Class_','',y) y = as.integer(y)-1 #xgboost take features in [0,numOfClass) x = rbind(train[,-ncol(train)],test) x = as.matrix(x) x = matrix(as.numeric(x),nrow(x),ncol(x)) trind = 1:length(y) teind = (nrow(train)+1):nrow(x) # Set necessary parameter param

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