Association Rules Flashcards

1
Q

Was ist unüberwachtes Lernen?

A
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2
Q

Was sind die zwei Aufgaben von Data Mining?

A
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3
Q

Zu welcher Aufgabe des Dataminings gehören supervised und unsupervised Learning jeweils?

A
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4
Q

Was ist time series prediction?

A
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5
Q

Was ist das Ziel von Descriptive Modeling?

A
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6
Q

Was ist Dependency Modeling?

A
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7
Q

Was ist Change- & Deviation Detection?

A
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8
Q

Was ist die Motivation von Frequent Pattern Analysis as Association Rules?

A

Finding inherent regularities in data

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9
Q

Beschreib KNN

A
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10
Q

Wann overfittet und underfittet KNN im Bezug auf k?

A
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11
Q

Wie funktioniert KNN für Regression?

A
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12
Q

Was ist Case Based Reasoning?

A
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13
Q

Beschreib den CBR Prozess

A
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14
Q

Was braucht man alles für CBR?

A
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15
Q

Was ist Support in Association Rules

A
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16
Q

Was ist Confidence in Association Rules?

A
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17
Q

Wie berechne ich Confidence basierend auf Support?

A
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18
Q

Was ist die downward closure property of frequent patterns?

A
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19
Q

Beschreib Apriori: a Candidate Generation & Test Approach

A
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20
Q

Major Clustering Approaches

Erkläre den Partitioning approach

A
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21
Q

Major Clustering Approaches

Erkläre den Hierarchical approach

A
22
Q

Major Clustering Approaches

Erkläre Model- or Neural Network based

A
23
Q

Major Clustering Approaches

Erkläre Instance-based

A
24
Q

Major Clustering Approaches

Erkläre den Density-based approach

A
25
Q

Major Clustering Approaches

Erkläre Dimensionality reduction methods

A
26
Q

Major Clustering Approaches

Erkläre Graph clustering

A
27
Q

Major Clustering Approaches

Erkläre den Grid-based approach

A
28
Q

Major Clustering Approaches

Erkläre Frequent pattern-based

A
29
Q

Wie kann man die Entfernung zwischen zwei Cluster bestimmen?

A
30
Q

Was ist ein Single Link?

A
31
Q

Was ist ein Complete link?

A
32
Q

Was ist die Entfernung über Centroids?

A
33
Q

Was ist die Entfernung über Medoids?

A
34
Q

Wie berechnet man einen Mean-Centroid?

A
35
Q

Wie berechnet man den Radius eines Clusters?

A
36
Q

Wie berechnet man den Diameter eines Clusters?

A
37
Q

Im Bezug auf intra-class und inter-class similarity? Wie schneiden gute Cluster ab?

A
38
Q

Beschreib den Davies-Boulding index

A
39
Q

Wie bestimmt man die Badness of separation of two clusters i, j?

A
40
Q

Wann ist der Davies-Bouldin index besser, klein oder groß?

A

klein

41
Q

Beschreib die Online Version des k-Means

A

Center wird nicht durch Mean der Datenpunkte in dem Cluster ersetzt, sondern:

42
Q

Wie lange wendet man die Regel an, des Online Version k-Means?

A
43
Q

Wieso konvergiert K-Means?

A
44
Q

Wie effizient in O-Notation ist der k-Means?

A
45
Q

Was sind Nachteile vom K-Means?

A
46
Q

Was ist K-medians?

A
47
Q

Was ist K-medoids?

A
48
Q

Was ist hierarchical clustering?

A
49
Q

Beschreib AGNES (Agglomerative Nesting)

A
50
Q

Beschreib DIANA (Divisive Analysis). Wie viele Wege gibt es bei n Datenpunkten zu teilen?

A