alfard

X=readcsv("e4.csv");
y2=readcsv("comparaisonY2.csv");
y3=readcsv("comparaisonY3.csv");
Result=rand(156849,1);
Result3=rand(156849,1);
tic();
for i= 1:156849
ensemblefity2=expm1(   (    y2[:,1]*X[i,1]  +    y2[:,2]*X[i,2]  +   y2[:,3]*X[i,3]   +  y2[:,4]*X[i,4] )/100)
T=[y2 ensemblefity2 ]
Result[i,:]=sqrt(   (1/size(T,1))    *   sum((      log(    T[:,6] +1    ) - log(   T[:,5]+1    )  ).^2))

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i=0
#mymat <- matrix(data=NA,nrow=1000000,ncol=6)
Score1 <- matrix(data=NA,nrow=156849,ncol=1)
Score2 <- matrix(data=NA,nrow=156849,ncol=1)

tic=proc.time()[3]

for (i in seq(1,nrow(e4),1))

alfard

x=[];

t_start = cputime;

for (i= 1 : 156849)

ensemblefity2=expm1(   (     y2(:,1)*e4(i,1)   +    y2(:,2)*e4(i,2)  +   y2(:,3)*e4(i,3)   +  y2(:,4)*e4(i,4) )/100);
ensemblefity3=expm1(   (     y3(:,1)*e4(i,1)   +    y3(:,2)*e4(i,2)  +   y3(:,3)*e4(i,3)   +  y3(:,4)*e4(i,4) )/100);

T=[y2 ensemblefity2 ];

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X=readcsv("e4.csv");
y2=readcsv("comparaisonY2.csv");
y3=readcsv("comparaisonY3.csv");
Result=rand(156849,1);
Result3=rand(156849,1);

tic();
for i= 1:156849

ensemblefity2=expm1(   (    y2[:,1]*X[i,1]  +    y2[:,2]*X[i,2]  +   y2[:,3]*X[i,3]   +  y2[:,4]*X[i,4] )/100)

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i=0
#mymat <- matrix(data=NA,nrow=1000000,ncol=6)
Score1 <- matrix(data=NA,nrow=156849,ncol=1)
Score2 <- matrix(data=NA,nrow=156849,ncol=1)

tic=proc.time()[3]

for (i in seq(1,nrow(e4),1))

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#include <iostream>
#define ARMA_NO_DEBUG

#include <armadillo>
#include <ctime>
#include <thread>


using namespace std;
using namespace arma;

alfard

#A noter sur python, on compte à partir de 0 et non de 1

import pandas as pd
import numpy as np
import csv


f = open('/home/alfard/Documents/Kaggle/Facebook2/Train.csv',"rb")
fw= open('/home/alfard/Documents/Kaggle/Facebook2/TrainClean.csv',"w")

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sample_train <- read.csv("/home/alfard/trainnrandom.csv",na.strings="NA")

sample_train$X <- NULL

sample_train$s1 <- ifelse (sample_train$click_bool==1 & sample_train$booking_bool==0,1,0)
sample_train$s2 <- ifelse (sample_train$click_bool==1 & sample_train$booking_bool==1,5,0)
sample_train$reli <- sample_train$s1+sample_train$s2

#sasfreq(reli,sample_train)
#sample_train$reli <- factor(sample_train$reli)

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dZ<-c("srch_id","reli")
d<-ST2[dZ]
d$reli<-as.numeric(d$reli)

dW<-c("srch_id","reli")
dr<-sample_train[dW]


###################################################################
d$V3<-NULL

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###############################################################################
####### MISE AU FORMAT LETOR ##################################################
ST4<-NULL
ST2<-NULL

#ec2-79-125-53-143.eu-west-1.compute.amazonaws.com

library(dummies)

library(gtools)