com.expleague.ml.cli.builders.methods.grid.GridBuilder Maven / Gradle / Ivy
package com.expleague.ml.cli.builders.methods.grid;
import com.expleague.commons.func.Factory;
import com.expleague.commons.math.vectors.impl.idxtrans.ArrayPermutation;
import com.expleague.ml.impl.BFGridImpl;
import com.expleague.ml.GridTools;
import com.expleague.ml.data.set.VecDataSet;
import com.expleague.ml.BFGrid;
import com.expleague.ml.impl.BFRowImpl;
import gnu.trove.list.array.TDoubleArrayList;
import gnu.trove.list.array.TIntArrayList;
import gnu.trove.set.hash.TIntHashSet;
import java.util.HashSet;
import java.util.Set;
public class GridBuilder implements Factory {
private BFGrid cooked;
private VecDataSet ds;
private Set catFeatureIds = new HashSet<>();
private Set ignoredColumns = new HashSet<>();
private final TIntHashSet known = new TIntHashSet();
private int binsCount = 32;
private int bfCount = 0;
private BFRowImpl[] rows;
private int oneHotLimit = 255;
//temp
private double[] feature;
public GridBuilder() {
}
public void setGrid(final BFGrid cooked) {
this.cooked = cooked;
}
public void setBinsCount(final int binsCount) {
this.binsCount = binsCount;
}
public void setDataSet(final VecDataSet dataSet) {
this.rows = new BFRowImpl[dataSet.xdim()];
this.ds = dataSet;
this.feature = new double[dataSet.length()];
}
public GridBuilder addCatFeatureIds(final Set catFeatureIds) {
this.catFeatureIds.addAll(catFeatureIds);
return this;
}
public GridBuilder addIgnoredColumns(final Set ignoredColumns) {
this.ignoredColumns.addAll(ignoredColumns);
return this;
}
@Override
public BFGrid create() {
if (cooked == null) {
cooked = build();
}
return cooked;
}
private BFGrid build() {
if (ds == null) {
throw new RuntimeException("Set dataset before build");
}
final int dim = ds.xdim();
for (int f = 0; f < dim; f++) {
if (ignoredColumns.contains(f)) {
continue;
}
if (catFeatureIds.contains(f)) {
addCatFeature(f);
}
else {
addFloatFeature(f);
}
}
return new BFGridImpl(rows);
}
private void addCatFeature(final int f) {
final double[] fakeBorders = GridTools.sortUnique(ds.data().col(f));
if (fakeBorders.length > oneHotLimit) {
throw new RuntimeException("Error: we support <255 cat features levels currently");
}
final boolean haveDiffrentElements = fakeBorders.length > 1;
if (!haveDiffrentElements) {
return;
}
rows[f] = new BFRowImpl(null, bfCount, f, fakeBorders, new int[fakeBorders.length], true);
bfCount += fakeBorders.length;
}
private void addFloatFeature(final int f) {
final ArrayPermutation permutation = new ArrayPermutation(ds.order(f));
final int[] order = permutation.direct();
final int[] reverse = permutation.reverse();
boolean haveDiffrentElements = false;
for (int i = 1; i < order.length; i++)
if (order[i] != order[0])
haveDiffrentElements = true;
if (!haveDiffrentElements) {
return;
}
for (int i = 0; i < feature.length; i++)
feature[i] = ds.at(order[i]).get(f);
final TIntArrayList borders = GridTools.greedyLogSumBorders(feature, binsCount);
final TDoubleArrayList dborders = new TDoubleArrayList();
final TIntArrayList sizes = new TIntArrayList();
{ // drop existing
final int[] crcs = new int[borders.size()];
for (int i = 0; i < ds.length(); i++) { // unordered index
final int orderedIndex = reverse[i];
for (int b = 0; b < borders.size() && orderedIndex >= borders.get(b); b++) {
crcs[b] = (crcs[b] * 31) + (i + 1);
}
}
for (int b = 0; b < borders.size() - 1; b++) {
if (known.contains(crcs[b]))
continue;
known.add(crcs[b]);
dborders.add(feature[borders.get(b) - 1]);
sizes.add(borders.get(b));
}
}
rows[f] = new BFRowImpl(bfCount, f, dborders.toArray(), sizes.toArray());
bfCount += dborders.size();
}
}
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