Knowledge Discovery and Data Mining I (wise18)

ADVANCED TOPICS cont. 2

(00:00:00) >: Process Mining

(00:42:31) >: Outlook

Recording from: 05.02.2019

Lecturer: Thomas, Seidl

CLASSIFICATION cont. 3 // REGRESSION // ADVANCED TOPICS

(00:00:00) >: Nearest Neighbor Classifiers

(00:11:37) >: Ensemble Classification

(00:38:26) >: Regression

(01:23:45) >: Process Mining

Recording from: 29.01.2019

Lecturer: Thomas, Seidl

CLASSIFICATION cont. 2

(00:00:00) >: Kernel Methods

(00:39:00) >: Decision Tree Classifiers

(01:56:33) >: Nearest Neighbor Classifiers

Recording from: 22.01.2019

Lecturer: Thomas, Seidl

CLASSIFICATION cont. 1

(00:00:00) >: Linear Discriminant Funktions

(00:58:12) >: Support Vector Machines

(01:32:21) >: Kernel Methods

Recording from: 15.01.2019

Lecturer: Thomas, Seidl

CLASSIFICATION

(00:00:00) >: Bayesian Classifiers

(02:18:23) >: Linear Discriminant Funktions

Recording from: 08.01.2019

Lecturer: Thomas, Seidl

CLUSTERING (Cont. IIII) // OUTLIER DETECTION

(00:00:00) >: Clustering

(01:00:14) >: Outlier Detection

Recording from: 18.12.2018

Lecturer: Dr. Peer Kröger

Clustering (Cont.III)

(00:00:00) >: 3.2 Clustering

(00:00:00) >: 3.2.6 Hierarchical Methods

(01:25:02) >: 3.2.7 Evaluation

Recording from: 11.12.2018

Lecturer: Thomas, Seidl

Clustering (Cont.II)

(00:00:00) >: 3.2.3 Density-Based Clustering

(00:21:26) >: Density-Based Clustering: DBSCAN Algorithm

(00:30:08) >: Determining the Parameters

(00:44:22) >: Database Support for Density-Based Clustering

(01:10:56) >: 3.2.4 Mean-Shift

(01:25:07) >: 3.2.5 Spectral Clustering

(02:06:02) >: 3.2.6 Hierarchical Methods

Recording from: 27.11.2018

Lecturer: Thomas, Seidl

Clustering (Cont.I)

(00:00:00) >: Clustering

Recording from: 20.11.2018

Lecturer: Thomas, Seidl

Frequent Pattern Mining // Clustering

(00:00:00) >: Frequent Pattern Mining

(01:46:15) >: Clustering

Recording from: 13.11.2018

Lecturer: Thomas, Seidl

Unsupervised Methods

(00:00:00) >: Frequent Pattern Mining

Recording from: 06.11.2018

Lecturer: Thomas, Seidl

BASICS // UNSUPERVISED METHODS

(00:00:00) >: Data Reduction

(00:18:11) >: Visualization

(00:47:23) >: Privacy

(01:16:20) >: Frequent Pattern Mining

Recording from: 30.10.2018

Lecturer: Thomas, Seidl

Basics (cont.)

(00:00:00) >: Data Representation

(00:47:01) >: Data Reduction

Recording from: 23.10.2018

Lecturer: Thomas, Seidl

Introduction // Basics

(00:00:00) >: Introduction, organisation, information regarding exam

(00:13:34) >: Motivation

(00:28:42) >: Knowledge Discovery Process

(01:30:53) >: Basics - Overview

(01:31:08) >: Data Representation

Recording from: 16.10.2018

Lecturer: Thomas, Seidl

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