README.md

dart_ml

Introduce machine learning to your dart supported apps from Android till Linux

Contents

• Algorithms

  • Classification

    • K-Nearest-Neigbor In statistics, the k-nearest neighbors algorithm (k-NN) is a non-parametric classification method
    • Logistic Regressor Logistic regression is a supervised learning classification algorithm generally used where we have to classify the data into two or more classes

  • Forecasting

    • Fit straight line A statistical approach towards forecasting, where a straight line is fit on the data to perform future predictions

  • Regression

    • Coming soon!

Example

Import package

    import 'package:dart_ml/dart_ml.dart';

Load dataset

    //Minimal dataset where each columns define the feature and the last row is the target class
    var dataset = [
               [2.7810836, 2.550537003, 0],
               [1.465489372, 2.362125076, 0],
               [3.396561688, 4.400293529, 0],
               [1.38807019, 1.850220317, 0],
               [3.06407232, 3.005305973, 0],
               [7.627531214, 2.759262235, 1],
               [5.332441248, 2.088626775, 1],
               [6.922596716, 1.77106367, 1],
               [8.675418651, -0.242068655, 1],
               [7.673756466, 3.508563011, 1]
                    ];

Using KNN algorithm

    var predicted = knn(dataset, dataset[0], 3); // (train, test, num_neighbors)
    print(predicted); //{0:5} 0 is the target class and 5 is the num of neigbors of the same class that is 0

Using Logistic regression

    var predicted = logreg(dataset, dataset[0], 0.3, 100)); // (train, test, l_rate, n_epoch)
    print(predicted); //0, returns the predicted class

Using Stline_forecast

    List dataset = [
	[2011, 80],
	[2012, 90],
	[2013, 92],
	[2014, 83],
	[2015, 94],
	[2016, 99],
	[2017, 92]
    ];
    var predicted = stline_forecast(dataset, 2018); // 98.0 predicted sales for the year 1995

Next Goals

• ⬜️ Regression Algorithms
• ⬜️ Neural Networks
• ⬜️ Model Evaluations
• ⬜️ Dataset tools

Contact

If you have questions, feel free to write me on

• Linkedin
• Instagram