public void TestXGBoostCreate()
{
var filename = @"../../../../datasets/xgboost/model_xbg_trees.txt";
var treesString = File.ReadAllText(filename);
var model = XGBoost.Create(treesString);
// TODO: ensure correctness of each tree
}
public void TestXGBoostEvaluateTiming()
{
var filename = @"../../../../datasets/xgboost/model_xbg_trees.txt";
var treesString = File.ReadAllText(filename);
var model = XGBoost.Create(treesString, prepareShrink: true);
var filename2 = @"../../../../datasets/xgboost/xgboost_test_cases_no_feature_names.txt";
var samplesString = File.ReadLines(filename2);
var samples = new Dictionary <string, float[]>();
foreach (var line in samplesString.Skip(1))
{
var parts = line.Split(',');
var sample = parts[0];
var featureIndex = int.Parse(parts[1]);
var value = float.Parse(parts[2]);
if (!samples.ContainsKey(sample))
{
samples.Add(sample, new float[1000]);
}
samples[sample][featureIndex] = value;
}
DoXGBoostEvaluateTimingFlatShrink(model, samples);
}
private static XGBoost GetModel(string dataPath, short[] reorderMapping)
{
var filename = Path.Combine(dataPath, @"model_xbg_trees.txt");
var treesString = File.ReadAllText(filename);
var model = XGBoost.Create(treesString);
if (reorderMapping != null)
{
model = FeatureReorderer.ReorderXGBoost(model, reorderMapping);
}
return(model);
}
public void TestXGBoostEvaluate()
{
var filename = @"../../../../datasets/xgboost/model_xbg_trees.txt";
var treesString = File.ReadAllText(filename);
var model = XGBoost.Create(treesString, prepareShrink: true);
var filename2 = @"../../../../datasets/xgboost/xgboost_test_cases_no_feature_names.txt";
var samplesString = File.ReadLines(filename2);
var samples = new Dictionary <string, float[]>();
foreach (var line in samplesString.Skip(1))
{
var parts = line.Split(',');
var sample = parts[0];
var featureIndex = int.Parse(parts[1]);
var value = float.Parse(parts[2]);
if (!samples.ContainsKey(sample))
{
samples.Add(sample, new float[1000]);
}
samples[sample][featureIndex] = value;
}
var timer = Stopwatch.StartNew();
const int probablity_feature_index = 840;
int i = 0;
for (; i < 2; i++)
{
foreach (var sample in samples)
{
var userFeatures = sample.Value.Take(639).ToArray();
var jobFeatures = sample.Value.Skip(639).ToArray();
var actual = model.EvaluateProbabilityFlatShrink(userFeatures, jobFeatures);
var expected = sample.Value[probablity_feature_index];
Assert.InRange(actual, expected - 1e-06, expected + 1e-06);
}
}
timer.Stop();
output.WriteLine($"Time taken for {i*samples.Count} evaluations: {timer.Elapsed.TotalMilliseconds} ms");
}
public void TestXGBoostEvaluateTimingReordered()
{
var filename1 = @"../../../../datasets/xgboost/reorder.csv";
var reorderMapping = File.ReadAllLines(filename1)
.Select(m => short.Parse(m))
.ToArray();
var filename = @"../../../../datasets/xgboost/model_xbg_trees.txt";
var treesString = File.ReadAllText(filename);
var model = XGBoost.Create(treesString);
model = FeatureReorderer.ReorderXGBoost(model, reorderMapping);
var filename2 = @"../../../../datasets/xgboost/xgboost_test_cases_no_feature_names.txt";
var samplesString = File.ReadLines(filename2);
var samples = new Dictionary <string, float[]>();
foreach (var line in samplesString.Skip(1))
{
var parts = line.Split(',');
var sample = parts[0];
var featureIndex = int.Parse(parts[1]);
if (featureIndex >= 0 && featureIndex < reorderMapping.Length)
{
featureIndex = reorderMapping[featureIndex];
}
var value = float.Parse(parts[2]);
if (!samples.ContainsKey(sample))
{
samples.Add(sample, new float[1000]);
}
samples[sample][featureIndex] = value;
}
DoXGBoostEvaluateTimingFlat(model, samples);
}