dart_ml

Description:

dart ml

dart_ml #
Introduce machine 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

Regression


Coming soon!








Example #
Import package #
import 'package:dart_ml/dart_ml.dart';
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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]
];

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

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

Contact #
If you have questions, feel free to write me on

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