Preskoči na glavno vsebino
e-učilnica UP FAMNIT
Slovenščina (sl)
English (en)
Slovenščina (sl)
Trenutno uporabljate gostujoči dostop (
Prijavite se
)
ELBA_Dushanbe
Domov
Predmeti
Razno
DIST
ELBA_Dushanbe
The data, ETL, visualization
Tutorial #2: EDA and data preparation
Tutorial #2: EDA and data preparation
The slides for "EDA and Descriptive Statistics" and "Data Preparation" + some sample data sets.
Prenesi mapo
Datasets
arrhythmia.arff
arrhythmia.csv
arrhythmia.names
bridges.arff
bridges.csv
bridges.data.version2
bridges.names
zoo.arff
zoo.csv
zoo.data
zoo.names
Slides
Practice02 - EDA and Statistics.pptx
Practice02 - Preparing the Data.pptx
◄ Exercise #1: A selected UCI ML data set in ARFF format
Skoči na ...
Skoči na ...
Announcements
Discussion
Re-training program (tentative)
Re-training agenda (tentative)
The CRISP-DM standard
What have I learned?
Input concepts
What have I learned?
Visualization
What have I learned?
Introduction to statistics
What have I learned?
Data preparation
What have I learned?
Tutorial #1: The Iris data set -- selected formats
Exercise #1: A selected UCI ML data set in ARFF format
Exercise #2: EDA and preparation on UCI ML Labor data set
Corpora
POS tagging / corpus tagging
Terminology
Text mining
Sketch engine workshop
Simple classification methods
What have I learned?
Decision trees -- introduction
What have I learned?
Decision trees -- the C4.5 algorithm
What have I learned?
Decision rules -- the covering algorithm
What have I learned?
Tutorial #3: Classification basics and Decision trees
Exercise #3: Classification algorithms -- basics
Tutorial #4: Classification -- the C4.5 algorithm
Exercise #4: Using J4.8 to model sample data
Tutorial #5: Decision rules -- the covering algorithm
Exercise #5: Using the PRISM algorithm to learn decision rules
Evaluation
Tutorial #6: Evaluation
Exercise #6: Comparing different evaluation strategies and measures
Regression and nearest neighbors
Tutorial #7: Regression and nearest neighbors
Exercise #7: Linear regression, the kNN algorithm
Exercise #2: EDA and preparation on UCI ML Labor data set ►