March 2019
Intermediate to advanced
368 pages
7h 53m
German
Content preview from Machine Learning Kochbuch
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KAPITEL 4
Numerische Daten verarbeiten
4.0Einführung
Quantitative Daten gehen auf Messungen zurück – ob es sich um Klassengrößen, monatliche Umsätze oder Schulnoten handelt. Naturgemäß drückt man diese Quantitäten numerisch aus (z.B. 29 Schüler, 529.392 Euro Umsatz usw.). In diesem Kapitel behandeln wir zahlreiche Strategien, um rohe numerische Daten in Merkmale zu überführen, die auf Algorithmen für maschinelles Lernen zugeschnitten sind.
4.1Ein Merkmal neu skalieren
Problem
Die Werte eines numerischen Merkmals sollen zwischen zwei Werten skaliert werden.
Lösung
Mit der MinMaxScaler-Implementierung der Bibliothek scikit-learn lässt sich ein Merkmalsarray skalieren:
# Bibliotheken laden
import numpy as np
from sklearn import preprocessing
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