grnn

Simple General Regression Neural Network for NodeJS

With and In-Built CSV Parser

## Description This is a NodeJS module to use GRNN to predict given a training data.

Check out the Wikipedia page to find out more about GRNN or the beginner stuffs here.

Applications of this Network can be found here .

Input Parameters

Required

double train_x : 2d array of n rows(training size) and m columns(features)
double train_y : 1d array of size n (actual output correspondng to each training input)
double test_x : 2d array of n1 rows(testing size) and m columns(features)
double test_y : 1d array of size n (actual output correspondng to each testing input)
double input : 1d array of size m (input data whose Y needs to be predicted)
double sigma : the value of sigma in the Radial Basis Function :: Standard Deviation
boolean normalize : whether to normalize train_x or not (generally normalization of training samples gives better predictions)

Functions

predict(input) - Returns predicted value of given input
mse() - Returns the Mean Squared Error for the given input

Variables

ypred[] - Array which have the predicted values for test input data
optimal_sigma - Value of Optimal Sigma ( Minimum MSE ) -- Must be used after calling mse() function

How to Use ? (Example)

Step 1 : Install module via npm

> npm install grnn

Step 2: Import module and use as follows

Or you can use it in your own code

const grnn = require("grnn"); 
const train_x = [[1, 2], [5, 6], [10, 11]],
  train_y = [3, 7, 12],
  input = [5.5, 6.5],
  sigma = 2.16,
  normalize = true;
const test_x = [[8.8, 9.8], [13, 14]];
const test_y = [10.8, 15];
const gr = new grnn(train_x, train_y, sigma, normalize, test_x, test_y);
const pred = gr.predict(input);
const mse = gr.mse();
console.log("Prediction:  " + pred);
console.log("MSE:  " + mse);
console.log("Optimal Value of Sigma:  " + gr.optimal_sigma);
console.log("Predicted Values against Test:  "+ gr.ypred);

If you are using CSV parser from file to load data

Here is a snapshot of a sample data.

Note that the Variable to be Predicted must be in the "LAST COLUMN" of the csv file.

Here's a sample code to use the built-in CSV parser

const grnn = require("grnn");
let gr = new grnn(); // initialize constructor with no parameters
const path="..../data.csv", // path to csv file
  header=true; // if your data contain headers
const data = gr.parseCSV(path, header);
const { train_x,  
        test_x, 
        train_y, 
        test_y } = gr.split_test_train(data); // attribute names are train_x, test_x, train_y, test_y
gr = new grnn(train_x, train_y, 0.1180, false, test_x, test_y); // initialized with actual parameters
const mse = gr.mse();
console.log("MSE:  " + mse);
console.log("Optimal Value of Sigma:  " + gr.optimal_sigma);
console.log("Predicted Values against Test:  "+gr.ypred.map(el=>el.toPrecision(4)));

Please contribute and raise issues. Pull requests are welcome.