Blog of Applied_Predictive_Model_11_chenshuai_2004

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I have been using Python/R/Shell for background development, but lack of communication. It’s the first time I try to post what I’m learning on the blog, hoping to get some guidance from the experts so that I can get some sunshine.

library(AppliedPredictiveModeling)
 data(concrete)

 library(caret)
 library(plyr)

head(concrete,2)

featurePlot(concrete[, -9], concrete$CompressiveStrength,
             between = list(x = 1, y = 1),
             type = c("g",  "p", "smooth"))

averaged <- ddply(mixtures,
                   .(Cement, BlastFurnaceSlag, FlyAsh, Water,
                     Superplasticizer, Coarse Aggregate,
                     FineAggregate, Age),
                   function(x) c(CompressiveStrength =
                     mean(x$CompressiveStrength)))

head(mixtures,2)

set.seed(975)
 inTrain <- createDataPartition(averaged$CompressiveStrength, p = 3/4)[[1]]
 training <- averaged[inTrain,]
 testing <- averaged[-inTrain,]

### Repeated Training/Test Splits

ctrl <- trainControl(method  = "repeatedcv", repeats = 5, number  span> = 10)

### Create a model formula that can be used repeatedly  

 modForm <- paste("CompressiveStrength ~ (.)^2 + I(Cement^2) + I(BlastFurnaceSlag^2) +",
                  "I(FlyAsh^2) + I(Water^2) + I(Superplasticizer^2) +  ",
                  "I(CoarseAggregate^2) + I(FineAggregate^2) + I(Age^2)"  )
 modForm <- as.formula(-  hljs-attribute">modForm)
 

### lm & pls: Partial Least Squares 

set.seed(669)
 lmFit <- train(modForm, data = training,
                method = "lm",
                trControl = ctrl)

 set.seed(669)
 plsFit <- train(modForm, data = training,
                 method = "pls",
                 preProc = c("center", "scale"),
                 tuneLength = 15,
                 trControl = ctrl)

Attaching package: 'pls'

 The following object is masked from 'package:caret':

     R2

 The following object is masked from 'package:stats':

     loads
 

### ridge regression

lassoGrid <- expand.grid(lambda = c(0, .001, .01, .1),
                          fraction = seq(0.05, 1, length = 20))
 set.seed(669)
 lassoFit <- train(modForm, data = training,
                   method = "enet",
                   preProc = c("center", "scale")  ,
                   tuneGrid = lassoGrid,
                   trControl = ctrl)
 

Loading required package: elasticnet
 

### Multivariate Adaptive Regression Splines

set.seed(669)
 earthFit <- train(CompressiveStrength ~ ., data = training,
                   method = "earth",
                   tuneGrid = expand.grid(degree = 1,
                                          nprune = 2:25),
                   trControl = ctrl)

Loading required package: earth
 Loading required package: plotmo
 Loading required package: plotrix
 Loading required package: TeachingDemos
 Warning message:
 "package 'TeachingDemos' was built under R version 3.2.5"
 

### SVM

 set.seed(669)
 svmRFit <- train(CompressiveStrength ~ ., data = training,
                  method = "svmRadial",
                  tuneLength = 15,
                  preProc = c("center", "scale")  ,
                  trControl = ctrl)
 

Loading required package: kernlab

 Attaching package: 'kernlab'

 The following object is masked from 'package:ggplot2':

     alpha
 

### neural network models
 ### don't run it due that it'll take more times!

nnetGrid <- expand.grid(decay = c(0.001, .01, .1),
                         size = seq(1, 27, by = 2),
                         bag = FALSE)
 set.seed(669)
 nnetFit <- train(CompressiveStrength ~ .,
                  data = training,
                  method = "avNNet",
                  tuneGrid = nnetGrid,
                  preProc = c("center", "scale")  ,
                  linout = TRUE,
                  trace = FALSE,
                  maxit = 50,
                  allowParallel = FALSE,
                  trControl = ctrl)

Loading required package: nnet
 

 set.seed(669)
 rpartFit <- train(CompressiveStrength ~ .,
                   data = training,
                   method = "rpart",
                   tuneLength = 30,
                   trControl = ctrl)
 

Loading required package: rpart
 

set.seed(669)
 treebagFit <- train(CompressiveStrength ~ .,
                     data = training,
                     method = "treebag",
                     trControl = ctrl)
 

Loading required package: ipred
 Warning message:
 "package 'ipred' was built under R version 3.2.5"Loading required package: e1071
 

set.seed(669)
 ctreeFit <- train(CompressiveStrength ~ .,
                   data = training,
                   method = "ctree",
                   tuneLength = 10,
                   trControl = ctrl)

Loading required package: party
 Warning message:
 "package 'party' was built under R version 3.2.5"Loading required package: grid
 Loading required package: mvtnorm
 Warning message:
 "package 'mvtnorm' was built under R version 3.3.0"Loading required package: modeltools
 Warning message:
 "package 'modeltools' was built under R version 3.2.5"Loading required package: stats4

 Attaching package: 'modeltools'

 The following object is masked from 'package:kernlab':

     prior

 The following object is masked from 'package:plyr':

     empty

 Loading required package: strucchange
 Warning message:
 "package 'strucchange' was built under R version 3.2.5"Loading required package: zoo

 Attaching package: 'zoo'

 The following objects are masked from 'package:base':

     as.Date, as.Dat

pan>=15,
preProc = c(“center”, “scale”) ,
trControl = ctrl)

Loading required package: kernlab

 Attaching package: 'kernlab'

 The following object is masked from 'package:ggplot2':

     alpha
 

### neural network models
 ### don't run it due that it'll take more times!

nnetGrid <- expand.grid(decay = c(0.001, .01, .1),
                         size = seq(1, 27, by = 2),
                         bag = FALSE)
 set.seed(669)
 nnetFit <- train(CompressiveStrength ~ .,
                  data = training,
                  method = "avNNet",
                  tuneGrid = nnetGrid,
                  preProc = c("center", "scale")  ,
                  linout = TRUE,
                  trace = FALSE,
                  maxit = 50,
                  allowParallel = FALSE,
                  trControl = ctrl)

Loading required package: nnet
 

 set.seed(669)
 rpartFit <- train(CompressiveStrength ~ .,
                   data = training,
                   method = "rpart",
                   tuneLength = 30,
                   trControl = ctrl)
 

Loading required package: rpart
 

set.seed(669)
 treebagFit <- train(CompressiveStrength ~ .,
                     data = training,
                     method = "treebag",
                     trControl = ctrl)
 

Loading required package: ipred
 Warning message:
 "package 'ipred' was built under R version 3.2.5"Loading required package: e1071
 

set.seed(669)
 ctreeFit <- train(CompressiveStrength ~ .,
                   data = training,
                   method = "ctree",
                   tuneLength = 10,
                   trControl = ctrl)

Loading required package: party
 Warning message:
 "package 'party' was built under R version 3.2.5"Loading required package: grid
 Loading required package: mvtnorm
 Warning message:
 "package 'mvtnorm' was built under R version 3.3.0"Loading required package: modeltools
 Warning message:
 "package 'modeltools' was built under R version 3.2.5"Loading required package: stats4

 Attaching package: 'modeltools'

 The following object is masked from 'package:kernlab':

     prior

 The following object is masked from 'package:plyr':

     empty

 Loading required package: strucchange
 Warning message:
 "package 'strucchange' was built under R version 3.2.5"Loading required package: zoo

 Attaching package: 'zoo'

 The following objects are masked from 'package:base':

     as.Date, as.Dat