Last data update: 2014.03.03

R: Compressive Strength of Concrete from Yeh (1998)
concreteR Documentation

Compressive Strength of Concrete from Yeh (1998)

Description

Yeh (1998) describes a collection of data sets from different sources that can be used for modeling the compressive strength of concrete formulations as a functions of their ingredients and age.

Usage

data(concrete)

Details

The data are from Yeh (1998) and taken from the UCI ML website http://archive.ics.uci.edu/ml/datasets/Concrete+Compressive+Strength.

There are 1030 data points from the UCI website, but the paper states that approximately 1,000 samples were made, but only 727 were analyzed in the source material. It is unclear which samples were excluded.

Value

concrete

data frame of data with predictor columns Cement, BlastFurnaceSlag, FlyAsh, Water, Superplasticizer, CoarseAggregate, FineAggregate and Age with response column CompressiveStrength. These are the amounts.

mixtures

The same data where all the ingredients have been converted to proportions of the total amounts.

Source

Yeh, I. C. (1998). Modeling of strength of high-performance concrete using artificial neural networks. Cement and Concrete Research, 28(12), 1797-1808. Elsevier.

Examples

data(concrete)

library(caret)

### Split used in the book:
set.seed(975)
inTrain <- createDataPartition(mixtures$CompressiveStrength, p = 3/4)[[1]]
training <- mixtures[ inTrain,]
testing  <- mixtures[-inTrain,]

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(AppliedPredictiveModeling)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AppliedPredictiveModeling/concrete.Rd_%03d_medium.png", width=480, height=480)
> ### Name: concrete
> ### Title: Compressive Strength of Concrete from Yeh (1998)
> ### Aliases: concrete mixtures
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(concrete)
> 
> library(caret)
Loading required package: lattice
Loading required package: ggplot2
> 
> ### Split used in the book:
> set.seed(975)
> inTrain <- createDataPartition(mixtures$CompressiveStrength, p = 3/4)[[1]]
> training <- mixtures[ inTrain,]
> testing  <- mixtures[-inTrain,]
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>