76 lines
2.4 KiB
Nim
76 lines
2.4 KiB
Nim
# Copyright 2023 Mattia Giambirtone
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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## Various data preprocessing tools
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import matrix
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import strformat
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import sets
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type
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LabelEncoder* = ref object
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## An encoder to assign a numerical value in the
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## range from 0 to n_labels - 1 to the labels
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## of some categorical data, reversibly
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isFit: bool
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labels: Matrix[string]
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proc newLabelEncoder*: LabelEncoder =
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## Initializes a new LabelEncoder object
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new(result)
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proc toOrderedSet[T](m: Matrix[T]): OrderedSet[T] =
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result = initOrderedSet[T]()
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for row in m:
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for element in row:
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result.incl(element)
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proc fit*(self: LabelEncoder, labels: Matrix[string]) =
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# Fits the encoder to the given labels
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var lbl: seq[string] = @[]
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for label in toOrderedSet(labels):
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lbl.add(label)
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self.labels = newMatrix(lbl)
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self.is_fit = true
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proc transform*(self: LabelEncoder, labels: Matrix[string]): Matrix[int] =
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## Transforms a vector of labels into a vector of encoded
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## integers. Duplicate labels are assigned the same integer
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assert self.isFit, "The estimator must be fit!"
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var res: seq[int] = @[]
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for row in labels:
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for label in row:
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if label notin self.labels:
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raise newException(ValueError, &"Unknown label '{label}'")
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res.add(self.labels.raw[].find(label))
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result = newMatrix(res)
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proc reverseTransform*(self: LabelEncoder, labels: Matrix[int]): Matrix[string] =
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## Reverses the transformation of the integer labels back to a string
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assert self.is_fit, "The estimator must be fit!"
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var res: seq[string] = @[]
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for row in labels:
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for label in row:
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if label notin 0..<self.labels.len():
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raise newException(ValueError, &"Unknown encoded label '{label}'")
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res.add(self.labels[0, label])
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result = newMatrix(res) |