summarizes the analytics-class class

Description

Returns a summary of the contents within an object of class analytics-class.

Usage

## S3 method for class 'analytics'
summary(object, ...)

Arguments

Author(s)

Timothy P. Jurka <tpjurka@ucdavis.edu>

Examples

library(RTextTools)
data(NYTimes)
data <- NYTimes[sample(1:3100,size=100,replace=FALSE),]
matrix <- create_matrix(cbind(data["Title"],data["Subject"]), language="english", 
removeNumbers=TRUE, stemWords=FALSE, weighting=tm::weightTfIdf)
container <- create_container(matrix,data$Topic.Code,trainSize=1:75, testSize=76:100, 
virgin=FALSE)
models <- train_models(container, algorithms=c("MAXENT","SVM"))
results <- classify_models(container, models)
analytics <- create_analytics(container, results)

summary(analytics)

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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> library(RTextTools)
Loading required package: SparseM

Attaching package: 'SparseM'

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

    backsolve

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/RTextTools/summary.analytics.Rd_%03d_medium.png", width=480, height=480)
> ### Name: summary.analytics
> ### Title: summarizes the 'analytics-class' class
> ### Aliases: summary.analytics
> ### Keywords: method
> 
> ### ** Examples
> 
> library(RTextTools)
> data(NYTimes)
> data <- NYTimes[sample(1:3100,size=100,replace=FALSE),]
> matrix <- create_matrix(cbind(data["Title"],data["Subject"]), language="english", 
+ removeNumbers=TRUE, stemWords=FALSE, weighting=tm::weightTfIdf)
> container <- create_container(matrix,data$Topic.Code,trainSize=1:75, testSize=76:100, 
+ virgin=FALSE)
> models <- train_models(container, algorithms=c("MAXENT","SVM"))
> results <- classify_models(container, models)
> analytics <- create_analytics(container, results)
> 
> summary(analytics)
ENSEMBLE SUMMARY

       n-ENSEMBLE COVERAGE n-ENSEMBLE RECALL
n >= 1                1.00              0.28
n >= 2                0.04              1.00


ALGORITHM PERFORMANCE

       SVM_PRECISION           SVM_RECALL           SVM_FSCORE 
               0.042                0.081                0.036 
MAXENTROPY_PRECISION    MAXENTROPY_RECALL    MAXENTROPY_FSCORE 
               0.237                0.233                0.214 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>