Learning Types Flashcards

1
Q

What are the main supervised learning tasks?

A

Classification and regression.

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2
Q

What are examples of supervised learning algorithms?

A
  • k-NN
  • Linear Regression
  • Logistic Regression
  • SVM
  • Decision Trees
  • Random Forest
  • NN
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3
Q

What are the common unsupervised learning tasks?

A
  • Clustering
  • Anomaly Detection
  • Visualization and Dimensionality Reduction
  • Association Rule Learning
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4
Q

What are some of the algorithms used in Clustering?

A
  • K-Means
  • DB-Scan
  • Hierarchical Clustering Analysis
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5
Q

What are some algorithms used for Anomaly Detection?

A
  • One-Class SVM

- Isolation Forest

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6
Q

What are some algorithms used for Visualization and Dimensionality Reduction?

A
  • Principle Component Analysis
  • Kernel PCA
  • Locally Linear Embedding
  • t-Distributed Stochastic Neighbour Embedding
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7
Q

What are some algorithms used for Association Rule Learning?

A
  • Apriori

- Eclat

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8
Q

What are the advantages to Online Learning?

A
  • Learning steps are faster and cheaper
  • Systems can independently adapt on the fly
  • Handles a continuous dataflow well
  • Memory efficient (used examples are discarded)
  • Useful for datasets too large to fit in memory
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9
Q

What are the challenges with Online Learning?

A
  • Setting the learning rate

- Large amounts of bad data will destroy system performance

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10
Q

What is the trade-off associated with the Learning Rate in Online learning?

A
  • Faster rates will learn new data quickly, but forget old data quickly too
  • Slower rates will learn new data slowly, but forget old data slowly too
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