predictor
A framework to automate the process of evaluating and running prediction models
npm install predictor
Want to see pretty graphs? Log in now!
2 | downloads in the last week |
4 | downloads in the last month |
Last Published By | |
---|---|
Version | 0.0.0 last updated 10 months ago |
Repository | https://github.com/mcwhittemore/predictor.git (git) |
Dependencies | None |
Starred by | mcwhittemore |
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
minusfrom
. Ifto
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.