GoLearn
=======
[](https://godoc.org/github.com/sjwhitworth/golearn)
[](https://travis-ci.org/sjwhitworth/golearn)
GoLearn is a 'batteries included' machine learning library for Go. **Simplicity**, paired with customisability, is the goal.
We are in active development, and would love comments from users out in the wild. Drop us a line on Twitter.
twitter: [@golearn_ml](http://www.twitter.com/golearn_ml)
Install
=======
```
go get github.com/sjwhitworth/golearn
cd src/github.com/sjwhitworth/golearn
go get ./...
```
Getting Started
=======
Data are loaded in as Instances. You can then perform matrix like operations on them, and pass them to estimators.
GoLearn implements the scikit-learn interface of Fit/Predict, so you can easily swap out estimators for trial and error.
GoLearn also includes helper functions for data, like cross validation, and train and test splitting.
```
// Load in a dataset, with headers. Header attributes will be stored.
// Think of instances as a Data Frame structure in R or Pandas.
// You can also create instances from scratch.
data, err := base.ParseCSVToInstances("datasets/iris_headers.csv", true)
// Print a pleasant summary of your data.
fmt.Println(data)
// Split your dataframe into a training set, and a test set, with an 80/20 proportion.
trainTest := base.InstancesTrainTestSplit(rawData, 0.8)
trainData := trainTest[0]
testData := trainTest[1]
// Instantiate a new KNN classifier. Euclidean distance, with 2 neighbours.
cls := knn.NewKnnClassifier("euclidean", 2)
// Fit it on your training data.
cls.Fit(trainData)
// Get your predictions against test instances.
predictions := cls.Predict(testData)
// Print a confusion matrix with precision and recall metrics.
confusionMat := evaluation.GetConfusionMatrix(testData, predictions)
fmt.Println(evaluation.GetSummary(confusionMat))
```
```
Iris-virginica 28 2 56 0.9333 0.9333 0.9333
Iris-setosa 29 0 59 1.0000 1.0000 1.0000
Iris-versicolor 27 2 57 0.9310 0.9310 0.9310
Overall accuracy: 0.9545
```
Examples
========
GoLearn comes with practical examples. Dive in and see what is going on.
```
cd examples/
go run knnclassifier_iris.go
go run instances.go
```
Join the team
=============
Please send me a mail at stephen dot whitworth at hailocab dot com.