emil: Evaluation of Modeling without Information Leakage

A toolbox for designing and evaluating predictive models with resampling methods. The aim of this package is to provide a simple and efficient general framework for working with any type of prediction problem, be it classification, regression or survival analysis, that is easy to extend and adapt to your specific setting. Some commonly used methods for classification, regression and survival analysis are included.

AuthorChristofer Backlin [aut, cre], Mats Gustafsson [aut]
Date of publication2016-06-21 07:48:48
MaintainerChristofer Backlin <emil@christofer.backlin.se>
LicenseGPL (>= 2)
Version2.2.6
https://github.com/Molmed/emil

View on CRAN

Man pages

as.modeling_procedure: Coerce to modeling procedure

dichotomize: Dichotomize time-to-event data

emil: Introduction to the emil package

error_fun: Performance estimation functions

evaluate: Evaluate a modeling procedure

extension: Extending the emil framework with user-defined methods

factor_to_logical: Convert factors to logicals

fill: Replace values with something else

fit: Fit a model

fit_caret: Fit a model using the 'caret' package

fit_cforest: Fit conditional inference forest

fit_coxph: Fit Cox proportional hazards model

fit_glmnet: Fit elastic net, LASSO or ridge regression model

fit_lda: Fit linear discriminant

fit_lm: Fit a linear model fitted with ordinary least squares

fit_naive_bayes: Fit a naive Bayes classifier

fit_pamr: Fit nearest shrunken centroids model.

fit_qda: Fit quadratic discriminant.

fit_randomForest: Fit random forest.

fit_rpart: Fit a decision tree

fit_svm: Fit a support vector machine

get_color: Get color palettes

get_importance: Feature (variable) importance of a fitted model

get_performance: Extract prediction performance

get_prediction: Extract predictions from modeling results

get_response: Extract the response from a data set

get_tuning: Extract parameter tuning statistics

image.resample: Visualize resampling scheme

importance_glmnet: Feature importance extractor for elastic net models

importance_pamr: Feature importance of nearest shrunken centroids.

importance_randomForest: Feature importance of random forest.

impute: Regular imputation

indent: Increase indentation

index_fit: Convert a fold to row indexes of fittdng or test set

is_blank: Wrapper for several methods to test if a variable is empty

is_constant: Check if an object contains more than one unique value

is_multi_procedure: Detect if modeling results contains multiple procedures

learning_curve: Learning curve analysis

list_method: List all available methods

log_message: Print a timestamped and indented log message

mode: Get the most common value

modeling_procedure: Setup a modeling procedure

na_index: Support function for identifying missing values

name_procedure: Get names for modeling procedures

neg_gmpa: Negative geometric mean of class specific predictive accuracy

nice_axis: Plots an axis the way an axis should be plotted.

nice_box: Plots a box around a plot

nice_require: Load a package and offer to install if missing

notify_once: Print a warning message if not printed earlier

pipe: Pipe operator

plot.learning_curve: Plot results from learning curve analysis

plot.Surv: Plot Surv vector

predict_caret: Predict using a 'caret' method

predict_cforest: Predict with conditional inference forest

predict_coxph: Predict using Cox proportional hazards model

predict_glmnet: Predict using generalized linear model with elastic net...

predict_lda: Prediction using already trained prediction model

predict_lm: Prediction using linear model

predict.model: Predict the response of unknown observations

predict_naive_bayes: Predict using naive Bayes model

predict_pamr: Prediction using nearest shrunken centroids.

predict_qda: Prediction using already trained classifier.

predict_randomForest: Prediction using random forest.

predict_rpart: Predict using a fitted decision tree

predict_svm: Predict using support vector machine

pre_factor_to_logical: Convert factors to logical columns

pre_impute: Basic imputation

pre_impute_df: Impute a data frame

pre_impute_knn: Nearest neighbors imputation

pre_log_message: Print log message during pre-processing

pre_pamr: PAMR adapted dataset pre-processing

pre_process: Data preprocessing

print.preprocessed_data: Print method for pre-processed data

pvalue: Extraction of p-value from a statistical test

pvalue.coxph: Extract p-value from a Cox proportional hazards model

pvalue.crr: Extracts p-value from a competing risk model

pvalue.cuminc: Extract p-value from a cumulative incidence estimation

pvalue.survdiff: Extracts p-value from a logrank test

resample: Resampling schemes

roc_curve: Calculate ROC curves

select: 'emil' and 'dplyr' integration

subresample: Generate resampling subschemes

subtree: Extract a subset of a tree of nested lists

trivial_error_rate: Calculate the trivial error rate

tune: Tune parameters of modeling procedures

validate_data: Validate a pre-processed data set

vlines: Add vertical or horizontal lines to a plot

weighted_error_rate: Weighted error rate

Files in this package

emil
emil/inst
emil/inst/CITATION
emil/tests
emil/tests/testthat.R
emil/tests/testthat
emil/tests/testthat/test-methods.r
emil/tests/testthat/test-resample.r
emil/tests/testthat/test-survival.r
emil/tests/testthat/test-modeling.r
emil/tests/testthat/test-preprocess.r
emil/tests/testthat/test-cppfunction.r
emil/tests/testthat/test-extractors.r
emil/tests/testthat/test-helpers.r
emil/tests/testthat/test-procedure.r
emil/tests/testthat/test-debug.r
emil/src
emil/src/is_constant.cpp
emil/src/RcppExports.cpp
emil/NAMESPACE
emil/NEWS.md
emil/R
emil/R/lda.r
emil/R/survival.r
emil/R/learning-curve.r
emil/R/lm.r
emil/R/glmnet.r
emil/R/rpart.r
emil/R/reshape-result.r
emil/R/imputation.r
emil/R/error-functions.r
emil/R/cforest.r
emil/R/RcppExports.R
emil/R/RcppWrappers.r
emil/R/modeling.r
emil/R/modeling_procedure.r
emil/R/plotting.r
emil/R/pamr.r
emil/R/resampling.r
emil/R/preprocessing.r
emil/R/randomForest.r
emil/R/caret.r
emil/R/roc-curve.r
emil/R/e1071.r
emil/R/helpers.r
emil/R/message.r
emil/R/qda.r
emil/MD5
emil/DESCRIPTION
emil/man
emil/man/index_fit.Rd emil/man/fit_randomForest.Rd emil/man/pre_impute.Rd emil/man/predict_lda.Rd emil/man/fit.Rd emil/man/nice_axis.Rd emil/man/pipe.Rd emil/man/predict_glmnet.Rd emil/man/tune.Rd emil/man/subtree.Rd emil/man/predict_coxph.Rd emil/man/predict.model.Rd emil/man/pvalue.survdiff.Rd emil/man/fit_pamr.Rd emil/man/error_fun.Rd emil/man/trivial_error_rate.Rd emil/man/learning_curve.Rd emil/man/weighted_error_rate.Rd emil/man/fit_lda.Rd emil/man/get_response.Rd emil/man/subresample.Rd emil/man/roc_curve.Rd emil/man/evaluate.Rd emil/man/get_tuning.Rd emil/man/predict_pamr.Rd emil/man/fit_qda.Rd emil/man/importance_randomForest.Rd emil/man/factor_to_logical.Rd emil/man/print.preprocessed_data.Rd emil/man/importance_pamr.Rd emil/man/nice_require.Rd emil/man/pre_pamr.Rd emil/man/is_constant.Rd emil/man/pvalue.crr.Rd emil/man/is_multi_procedure.Rd emil/man/get_prediction.Rd emil/man/validate_data.Rd emil/man/predict_cforest.Rd emil/man/plot.learning_curve.Rd emil/man/get_importance.Rd emil/man/na_index.Rd emil/man/dichotomize.Rd emil/man/resample.Rd emil/man/fit_glmnet.Rd emil/man/pre_impute_knn.Rd emil/man/fit_naive_bayes.Rd emil/man/pre_log_message.Rd emil/man/extension.Rd emil/man/is_blank.Rd emil/man/indent.Rd emil/man/mode.Rd emil/man/get_performance.Rd emil/man/neg_gmpa.Rd emil/man/image.resample.Rd emil/man/predict_caret.Rd emil/man/pre_impute_df.Rd emil/man/predict_randomForest.Rd emil/man/name_procedure.Rd emil/man/impute.Rd emil/man/vlines.Rd emil/man/fit_cforest.Rd emil/man/fit_rpart.Rd emil/man/plot.Surv.Rd emil/man/pvalue.coxph.Rd emil/man/pre_factor_to_logical.Rd emil/man/pre_process.Rd emil/man/fill.Rd emil/man/as.modeling_procedure.Rd emil/man/modeling_procedure.Rd emil/man/get_color.Rd emil/man/fit_coxph.Rd emil/man/fit_caret.Rd emil/man/predict_naive_bayes.Rd emil/man/notify_once.Rd emil/man/nice_box.Rd emil/man/importance_glmnet.Rd emil/man/predict_qda.Rd emil/man/pvalue.cuminc.Rd emil/man/fit_lm.Rd emil/man/predict_rpart.Rd emil/man/list_method.Rd emil/man/predict_lm.Rd emil/man/pvalue.Rd emil/man/log_message.Rd emil/man/predict_svm.Rd emil/man/select.Rd emil/man/fit_svm.Rd emil/man/emil.Rd

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