chore: add examples

example_test.go

@@ -0,0 +1,27 @@
+package arboreal_test
+
+import (
+	"github.com/stillmatic/arboreal"
+	"github.com/stretchr/testify/assert"
+	"testing"
+)
+
+func TestXGBoostSchema_Predict(t *testing.T) {
+	schema, err := arboreal.NewGBDTFromXGBoostJSON("testdata/regression.json")
+	assert.NoError(t, err)
+	inpArr := []float32{0.1, 0.2, 0.3, 0.4, 0.5}
+	inpVec := arboreal.SparseVectorFromArray(inpArr)
+	res, err := schema.Predict(inpVec)
+	assert.NoError(t, err)
+	assert.InDelta(t, 6.245257, res[0], 0.000001)
+}
+
+func TestOptimizedGBTModel(t *testing.T) {
+	res, err := arboreal.NewGBDTFromXGBoostJSON("testdata/mortgage_xgb.json")
+	assert.NoError(t, err)
+	newRes := arboreal.NewOptimizedGBDTClassifierFromSchema(res)
+
+	vec := make(arboreal.SparseVector, 44)
+	_, err = newRes.Predict(vec)
+	assert.NoError(t, err)
+}

readme.md

@@ -8,6 +8,10 @@ Pure Go library for gradient boosted decision trees. The library is optimized fo
 
 # Usage
 
+```bash
+go get github.com/stillmatic/arboreal
+```
+
 ```go
 res, err := arboreal.NewGBDTFromXGBoostJSON("testdata/regression.json")
 inpArr := []float32{0.1, 0.2, 0.3, 0.4, 0.5}

xgboost.go

@@ -1,3 +1,4 @@
+// Package arboreal is a pure Go package for XGBoost model inference.
 package arboreal
 
 import (

xgboostio.go

@@ -1,7 +1,8 @@
+package arboreal
+
 // IO for XGBoost JSON files
 // see https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html
 // https://github.com/dmlc/xgboost/blob/24c237308097b693b744af2ad1f86f44be068523/demo/json-model/json_parser.py
-package arboreal
 
 import (
 	"encoding/json"
@@ -12,7 +13,7 @@ import (
 	"github.com/pkg/errors"
 )
 
-// custom JSON unmarshal for learner
+// UnmarshalJSON is a custom JSON unmarshal for learner
 func (l *learner) UnmarshalJSON(b []byte) error {
 	var tmp struct {
 		FeatureNames      []featureName     `json:"feature_names,omitempty"`