blob: 11461731b3438857970174195d8d2d668dbb6b61 [file] [log] [blame]
#-------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
#-------------------------------------------------------------
# Apply robust scaling using precomputed medians and IQRs
#
# INPUT:
# -------------------------------------------------------------------------------------
# X Input feature matrix of shape n-by-m
# med Column medians (Q2) of shape 1-by-m
# q1 Column first quantiles (Q1) of shape 1-by-m
# q3 Column first quantiles (Q3) of shape 1-by-m
# -------------------------------------------------------------------------------------
#
# OUTPUT:
# -------------------------------------------------------------------------------------
# Y Scaled output matrix of shape n-by-m
# -------------------------------------------------------------------------------------
m_scaleRobustApply = function(Matrix[Double] X, Matrix[Double] med, Matrix[Double] q1, Matrix[Double] q3)
return (Matrix[Double] Y)
{
iqr = q3 - q1
# Ensure robust scaling is safe by replacing invalid IQRs
iqr = replace(target=iqr, pattern=0, replacement=1)
iqr = replace(target=iqr, pattern=NaN, replacement=1)
# Apply robust transformation
Y = (X - med) / iqr
}