Showing 4 open source projects for "error"

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    Veeam Data Platform v13.1 - Get Your Free Trial

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    Train ML Models With SQL You Already Know

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    ShinyItemAnalysis

    ShinyItemAnalysis

    Test and Item Analysis via Shiny

    ShinyItemAnalysis is an R package including functions and interactive shiny application for the psychometric analysis of educational tests, psychological assessments, health-related and other types of multi-item measurements, or ratings from multiple raters. Exploration of total and standard scores. Analysis of measurement error and reliability. Analysis of correlation structure and validity. Traditional item analysis. Item analysis with regression models. Item analysis with IRT models. Detection of differential item functioning. Number of toy datasets is available, the interactive application also allows the users to upload and analyze their own data and to automatically generate PDF or HTML reports. ...
    Downloads: 1 This Week
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  • 2
    forecast

    forecast

    Forecasting Functions for Time Series and Linear Models

    ...It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual checks, model accuracy, plots, forecast error measures etc.
    Downloads: 0 This Week
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  • 3
    Readr

    Readr

    Read flat files (csv, tsv, fwf) into R

    readr is an R package that provides a fast and friendly way to read rectangular data, such as CSV and TSV files. Part of the Tidyverse, it simplifies data import and parsing tasks in R.​
    Downloads: 3 This Week
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  • 4
    mlr

    mlr

    Machine Learning in R

    R does not define a standardized interface for its machine-learning algorithms. Therefore, for any non-trivial experiments, you need to write lengthy, tedious, and error-prone wrappers to call the different algorithms and unify their respective output. {mlr} provides this infrastructure so that you can focus on your experiments! The framework provides supervised methods like classification, regression, and survival analysis along with their corresponding evaluation and optimization methods, as well as unsupervised methods like clustering. ...
    Downloads: 0 This Week
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