an S4 class containing the analytics for a classified set of documents.

Description

An S4 class containing the analytics for a classified set of documents. This includes a label summary, document summary, ensemble summary, and algorithm summary. This class is returned if virgin=FALSE in create_container.

Objects from the Class

Objects could in principle be created by calls of the form new("analytics", ...). The preferred form is to have them created via a call to create_analytics.

Slots

label_summary

Object of class "data.frame": stores the analytics for each label, including the percent coded accurately and how much overcoding occurred

document_summary

Object of class "data.frame": stores the analytics for each document, including all available raw data associated with the learning process

algorithm_summary

Object of class "data.frame": stores precision, recall, and F-score statistics for each algorithm, broken down by label

ensemble_summary

Object of class "matrix": stores the accuracy and coverage for an n-algorithm ensemble scoring

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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'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.

> 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/analytics-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: analytics-class
> ### Title: an S4 class containing the analytics for a classified set of
> ###   documents.
> ### Aliases: analytics-class
> ### Keywords: classes
> 
> ### ** 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                 1.0              0.32
n >= 2                 0.2              0.60


ALGORITHM PERFORMANCE

       SVM_PRECISION           SVM_RECALL           SVM_FSCORE 
          0.05416667           0.10666667           0.07083333 
MAXENTROPY_PRECISION    MAXENTROPY_RECALL    MAXENTROPY_FSCORE 
          0.18833333           0.17666667           0.16750000 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>