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    predictorpublic

    Predictor

    Predictor automates the process of predicting future values in a set and evaluating this prediction models. Predictor doesn't predict the values for you but rather sets up a few tools to help you test and run your prediction functions. The base functions are guess and evaluate. Predictor also comes with a set of standard numeric datasets including but not limited to the s-curve, parabola, and Fibonacci sets. These can be found under the static datasets namespace.

    Install

    npm install predictor
    

    Usage

    var predictor = require("predictor");
     
    var guesser = function(distance, dataset){
        return dataset[dataset.length-1]+distance;
    }
     
    var sCurvePredictor = new predictor(predictor.datasets.s_curve, guesser, predictor.evaluators.standard);
     
    var evaluation = sCurvePredictor.evaluate({distance:3});
     
    console.log(evaluation);

    Predictor Object

    new predictor(dataset, guesser, evaluator)

    Creates a new predictor object.

    • dataset: the array of data the guesser is trying to predict.
    • guesser(distance, dataset): a function that guesses the array value of the dataset at x distance out;
      • distance: is the number of iterations out the guesser is trying to predict.
      • dataset: all historical data points up to and including the predict from point.
    • evaluator(guess, answer): returns a numeric representation of how accurate the guess was.
      • guess: a result of guesser
      • answer: the actually value from the dataset at the same location guesser tried to predict.

    obj.guess(opt)

    Guesses a value based on the supplied options.

    Options

    • dataset: full dataset. Should included all datapoints up to the guess from point and can include more. Defaults to dataset provided in the initializer.
    • from: Where in the dataset to guess from. Defaults to the end of the dataset.
    • to: Where in the dataset to guess. Will have no effect if distance is provided.
    • distance: how far from the from point to guess. If not provided will default to the value of to minus from. If to is undefined, distance will default to 1.
    • guesser: a guesser function. Defaults to the one provided in the initializer.

    obj.evaluate();

    Evaluates a guesser function based on the supplied options. Returns an object of observations included the average evaluation, a list of guesses resulting in NaN and a record of each iteration through the dataset, guess, answer and evaluation.

    Options

    • dataset: Full dataset. Should included all datapoints up to the guess from point and can include more. Defaults to dataset provided in the initializer.
    • distance: How far from the from point to guess. If not provided will default 1.
    • guesser: a guesser function. Defaults to the one provided in the initializer.
    • evaluator: an evaluator function. Defaults to the one provided in the initializer.

    Static Values

    predictor.datasets

    A collection of predefined numeric sets.

    • predictor.datasets.S_CURVE:
    • predictor.datasets.PARABOLA:
    • predictor.datasets.FIBONACCI:

    predictor.evaluators

    A collection of predefined evaluators

    • predictor.evaluators.standard: evaluates the guess as a percentage away from the answer. 0 is a perfect score. 100 means the guess is as far from the answer as the answer is from 0.

    Keywords

    none

    install

    npm i predictor

    Downloadsweekly downloads

    4

    version

    0.0.0

    license

    none

    repository

    githubgithub

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