SVM Tools provide some simple node wrappers around libsvm to train and test models.
- Install libsvm
- Ensure that
svm-train
andsvm-predict
are in the executable path - Install node and npm
- Install svm-tools:
npm i -g svm-tools
Generate a model:
svm-gen [train.csv|json] [model.json]
Test a generated model:
svm-test [test.csv|json] [model.json] [report.csv]
Train/Test File Format (CSV):
- First element is the zone label
- Other elements are beacon measurements of the form BEACONID:RSSI
- Alternatively, a JSON file using the testdata object format described below can be used as input.
Example:
1,1-2:-71,1-1:-69,1-3:-86,1-4:-88
Model File Format
{
"simple": {
"mapping": {
"1-1": "Zone A",
"1-2": "Zone B"
}
},
"svm": {
"mapping": {
"1-1": 1,
"1-2": 2
},
"zones": ["Zone A", "Zone B"],
"model": "..."
}
}
var svmTools = require('svm-tools');
// generate a model
svmTools.train(data, progressCallback).then(function (model) { ... });
// test a model
svmTools.test(data, model).then(function (report) { ... });
Testdata Object:
[{
"zone": "Zone A",
"data": [{
"date": "2012-04-23T18:25:43.511Z",
"gps": {
"east": 4.1237372,
"north": 10.28288382,
"accuracy": 1
},
"beacons": [{
"uuid": "123e4567-e89b-12d3-a456-426655440000",
"major": 1,
"minor": 1,
"rssi": -87
}]
}]
}]
Model Object (see description in section CLI Usage).
convert.js
converts a legacy .csv file (from the BeaconScanner, see that repository) into one that can be used by svm-genconvertCSV.js
converts the result of convert.js into a json that can be imported into an inform-location-server (see that repository)
Copyright (c) 2015 Jonathan Diehl
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