4 writes to Features
Microsoft.ML.Data (1)
Training\TrainerUtils.cs (1)
855_get(ref Features);
Microsoft.ML.KMeansClustering (2)
KMeansPlusPlusTrainer.cs (2)
418Utils.Swap(ref cursor.Features, ref candidate); 1737mapper(ref cur.Features, rowIndexGetter(cur), innerWorkState, rand);
Microsoft.ML.StandardTrainers (1)
Standard\LogisticRegression\LbfgsPredictorBase.cs (1)
629Utils.Swap(ref _features[index], ref cursor.Features);
71 references to Features
Microsoft.ML.Data (1)
Training\TrainerUtils.cs (1)
856if (!_keepBad && !FloatUtils.IsFinite(Features.GetValues()))
Microsoft.ML.Ensemble (3)
OutputCombiners\BaseStacking.cs (2)
188EnsembleUtils.SelectFeatures(in cursor.Features, model.SelectedFeatures, model.Cardinality, ref vBuffers[i]); 192maps[i](in cursor.Features, ref predictions[i]);
Selector\SubModelSelector\BaseDiverseSelector.cs (1)
54map(in cursor.Features, ref preds[count]);
Microsoft.ML.FastTree (3)
FastTree.cs (2)
1874foreach (var kvp in cursor.Features.Items()) 1881featureValues += cursor.Features.GetValues().Length;
GamModelParameters.cs (1)
662var score = _pred.GetFeatureBinsAndScore(in cursor.Features, bins);
Microsoft.ML.KMeansClustering (10)
KMeansPlusPlusTrainer.cs (10)
383if (dimensionality != cursor.Features.Length) 388cursor.Features.Length); 394l2 = VectorUtils.NormSquared(cursor.Features); 399var distance = -2 * VectorUtils.DotProduct(in cursor.Features, in centroids[j]) 1425VectorUtils.Add(in cursor.Features, ref cachedSumCopy[state.GetBestCluster(id)]); 1503state.AssertValidYinYangBounds(n, in cursor.Features, centroids); 1513KMeansUtils.FindBestCluster(in cursor.Features, centroids, centroidL2s, k, false, out minDistance, out cluster, out secMinDistance, out secCluster); 1516chunkState.UpdateClusterAssignment(in cursor.Features, cluster, minDistance); 1519int prevCluster = state.SetYinYangCluster(n, in cursor.Features, minDistance, cluster, secMinDistance); 1520chunkState.UpdateClusterAssignment(firstIteration, in cursor.Features, cluster, prevCluster, minDistance);
Microsoft.ML.LightGbm (11)
LightGbmTrainerBase.cs (11)
755nonZeroCount += cursor.Features.GetValues().Length; 756totalCount += cursor.Features.Length; 848var cursorFeaturesValues = cursor.Features.GetValues(); 887var cursorFeaturesValues = cursor.Features.GetValues(); 888var cursorFeaturesIndices = cursor.Features.GetIndices(); 966if (cursor.Features.IsDense) 1095if (numElem + cursor.Features.GetValues().Length > features.Length) 1138if (cursor.Features.IsDense) 1166cursor.Features.CopyTo(features, numElem, 0.0f); 1174int numValue = cursor.Features.GetValues().Length; 1180if (cursor.Features.IsDense)
Microsoft.ML.Mkl.Components (11)
OlsLinearRegression.cs (7)
234var values = cursor.Features.GetValues(); 236if (cursor.Features.IsDense) 247var indices = cursor.Features.GetIndices(); 317var values = cursor.Features.GetValues(); 319if (cursor.Features.IsDense) 340var fIndices = cursor.Features.GetIndices(); 464var features = cursor.Features;
SymSgdClassificationTrainer.cs (4)
593var featureValues = _cursor.Features.GetValues(); 613if (!_cursor.Features.IsDense) 615couldLoad = _instIndices.AddToStorage(_cursor.Features.GetIndices()); 624InstanceProperties prop = new InstanceProperties(featureCount, label, _cursor.Features.IsDense);
Microsoft.ML.OneDal (3)
OneDalUtils.cs (3)
55var values = cursor.Features.GetValues(); 56if (cursor.Features.IsDense) 67var indices = cursor.Features.GetIndices();
Microsoft.ML.PCA (3)
PcaTrainer.cs (3)
318VectorUtils.AddMult(in cursor.Features, cursor.Weight, ref mean); 322in cursor.Features, 324cursor.Weight * VectorUtils.DotProduct(omega[i], in cursor.Features));
Microsoft.ML.StandardTrainers (26)
LdSvm\LdSvmTrainer.cs (1)
517cursor.Features.CopyTo(ref example.Features);
Standard\LogisticRegression\LbfgsPredictorBase.cs (6)
392AccumulateOneGradient(in cursor.Features, cursor.Label, cursor.Weight, in x, ref grad, ref scratch); 506var values = cursor.Features.GetValues(); 507if (cursor.Features.IsDense) 518var indices = cursor.Features.GetIndices(); 616PreTrainingProcessInstance(cursor.Label, in cursor.Features, cursor.Weight); 876loss += AccumulateOneGradient(in cursor.Features, cursor.Label, cursor.Weight,
Standard\LogisticRegression\LogisticRegression.cs (8)
349var score = bias + VectorUtils.DotProductWithOffset(in CurrentWeights, 1, in cursor.Features); 356var values = cursor.Features.GetValues(); 357if (cursor.Features.IsDense) 366Contracts.Assert(0 <= wi && wi < cursor.Features.Length); 374Contracts.Assert(0 <= wj && wj < cursor.Features.Length); 382var indices = cursor.Features.GetIndices(); 390Contracts.Assert(0 < wi && wi <= cursor.Features.Length); 403Contracts.Assert(0 < wj && wj <= cursor.Features.Length);
Standard\MulticlassClassification\MulticlassNaiveBayesTrainer.cs (3)
176var featureValues = cursor.Features.GetValues(); 177if (cursor.Features.IsDense) 187var featureIndices = cursor.Features.GetIndices();
Standard\Online\OnlineLinear.cs (1)
336state.ProcessDataInstance(ch, in cursor.Features, cursor.Label, cursor.Weight);
Standard\SdcaBinary.cs (5)
582var features = cursor.Features; 816VBuffer<float> features = cursor.Features; 980var features = cursor.Features; 2084var features = cursor.Features; 2123VBuffer<float> features = cursor.Features;
Standard\SdcaMulticlass.cs (2)
206var features = cursor.Features; 381var features = cursor.Features;