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Introduction to Machine Learning Algorithms
What is Artificial Intelligence (AI)? ,[object Object],[object Object],[object Object]
Research Areas and Approaches Artificial Intelligence Research Rationalism (Logical) Empiricism (Statistical) Connectionism (Neural) Evolutionary (Genetic) Biological (Molecular) Paradigm Application Intelligent Agents Information Retrieval Electronic Commerce Data Mining Bioinformatics Natural Language Proc. Expert Systems Learning Algorithms Inference Mechanisms Knowledge Representation Intelligent System Architecture
Concept of Machine Learning
                                              
Context Information Theory Computer Science (AI) Cognitive Science Statistics Machine Learning
Why Machine Learning? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Learning: Definition ,[object Object],[object Object],the improvement of behavior on some performance task through acquisition of knowledge based on partial task experience
A Learning Problem: EnjoySport Sky What is the general concept? Temp Humid Wind Water Forecast EnjoySports Sunny Warm Normal Strong Warm Same Yes Sunny Warm High Strong Warm Same Yes Rainy Cold High Strong Warm Change No Sunny Warm High Strong Cool Change Yes
Metaphors and Methods Neurobiology Biological Evolution Heuristic Search Statistical Inference Memory and Retrieval Connectionist Learning Genetic Learning Tree / Rule Induction Case-Based Learning Probabilistic Induction
What is the Learning Problem? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Machine Learning: Tasks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Machine Learning: Strategies ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Supervised Learning ,[object Object],[object Object]
Examples of Input-Output Pairs Task Inputs Outputs Recognition Action Janitor robot problem Descriptions of objects Classes that the objects belong to Actions or predictions Descriptions of situations Descriptions of offices (floor, prof’s office) Yes or No (indicating whether or not the office contains a recycling bin)
Unsupervised Learning ,[object Object],[object Object],[object Object],[object Object]
Online and Batch Learning ,[object Object],[object Object],[object Object],[object Object]
Machine Learning Algorithms and Applications
Machine Learning Algorithms ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Neural Nets for Handwritten Digit Recognition ,[object Object],… Pre-processing … … … Input units Hidden units Output units 0 1 2 3 9 … Training Test … … … 0 1 2 3 9 ? …
ALVINN System: Neural Network Learning to Steer an Autonomous Vehicle
Learning to Navigate a Vehicle by Observing an Human Expert (1/2) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Learning to Navigate a Vehicle by Observing an Human Expert (2/2)
Data Recorrection by a Hopfield Network original target data corrupted input data Recorrected data after 10 iterations Recorrected data after 20 iterations Fully recorrected data after 35 iterations
ANN for Face Recognition 960 x 3 x 4 network is trained on gray-level images of faces to predict whether a person is looking to their left, right, ahead, or up.
Data Mining -- -- -- -- -- -- -- -- -- Target data Cleaned data Transformed data Patterns/ model Knowledge Database/data warehouse Selection & Sampling Preprocessing & Cleaning Transformation & reduction Interpretation/ Evaluation Data Mining Performance system
Hot Water Flashing Nozzle with Evolutionary Algorithms Start Hot water entering Steam and droplet at exit At throat: Mach 1 and onset of flashing Hans-Paul Schwefel performed the original experiments
Machine Learning Applications in Bioinformatics
Bayesian Networks for Gene Expression Analysis ,[object Object],[object Object],Processed data Data Preprocessing Learning algorithm Gene C Gene B Gene A Target Gene D Gene C Gene B Gene A Target Gene D Gene C Gene B Gene A Target Gene D Gene C Gene B Gene A Target Gene D The values of Gene C and Gene B are given. Belief propagation Probability for the target is computed.
Multilayer Perceptrons for Gene Finding and Prediction bases Discrete exon score 0 1 sequence score Coding potential value GC Composition Length Donor Acceptor Intron vocabulary
Self-Organizing Maps for DNA Microarray Data Analysis Two-dimensional array of postsynaptic neurons Bundle of synaptic connections Winning neurons Input
Biological Information Extraction Database Template Filling Data Analysis & Field Identification Data Classification & Field Extraction Information Extraction Field Property Identification & Learning Text Data DB Location Date DB Record
Biomolecular Computing 011001101010001 ATGCTCGAAGCT

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Machine Learning

  • 1. Introduction to Machine Learning Algorithms
  • 2.
  • 3. Research Areas and Approaches Artificial Intelligence Research Rationalism (Logical) Empiricism (Statistical) Connectionism (Neural) Evolutionary (Genetic) Biological (Molecular) Paradigm Application Intelligent Agents Information Retrieval Electronic Commerce Data Mining Bioinformatics Natural Language Proc. Expert Systems Learning Algorithms Inference Mechanisms Knowledge Representation Intelligent System Architecture
  • 6. Context Information Theory Computer Science (AI) Cognitive Science Statistics Machine Learning
  • 7.
  • 8.
  • 9. A Learning Problem: EnjoySport Sky What is the general concept? Temp Humid Wind Water Forecast EnjoySports Sunny Warm Normal Strong Warm Same Yes Sunny Warm High Strong Warm Same Yes Rainy Cold High Strong Warm Change No Sunny Warm High Strong Cool Change Yes
  • 10. Metaphors and Methods Neurobiology Biological Evolution Heuristic Search Statistical Inference Memory and Retrieval Connectionist Learning Genetic Learning Tree / Rule Induction Case-Based Learning Probabilistic Induction
  • 11.
  • 12.
  • 13.
  • 14.
  • 15. Examples of Input-Output Pairs Task Inputs Outputs Recognition Action Janitor robot problem Descriptions of objects Classes that the objects belong to Actions or predictions Descriptions of situations Descriptions of offices (floor, prof’s office) Yes or No (indicating whether or not the office contains a recycling bin)
  • 16.
  • 17.
  • 18. Machine Learning Algorithms and Applications
  • 19.
  • 20.
  • 21. ALVINN System: Neural Network Learning to Steer an Autonomous Vehicle
  • 22.
  • 23. Learning to Navigate a Vehicle by Observing an Human Expert (2/2)
  • 24. Data Recorrection by a Hopfield Network original target data corrupted input data Recorrected data after 10 iterations Recorrected data after 20 iterations Fully recorrected data after 35 iterations
  • 25. ANN for Face Recognition 960 x 3 x 4 network is trained on gray-level images of faces to predict whether a person is looking to their left, right, ahead, or up.
  • 26. Data Mining -- -- -- -- -- -- -- -- -- Target data Cleaned data Transformed data Patterns/ model Knowledge Database/data warehouse Selection & Sampling Preprocessing & Cleaning Transformation & reduction Interpretation/ Evaluation Data Mining Performance system
  • 27. Hot Water Flashing Nozzle with Evolutionary Algorithms Start Hot water entering Steam and droplet at exit At throat: Mach 1 and onset of flashing Hans-Paul Schwefel performed the original experiments
  • 28. Machine Learning Applications in Bioinformatics
  • 29.
  • 30. Multilayer Perceptrons for Gene Finding and Prediction bases Discrete exon score 0 1 sequence score Coding potential value GC Composition Length Donor Acceptor Intron vocabulary
  • 31. Self-Organizing Maps for DNA Microarray Data Analysis Two-dimensional array of postsynaptic neurons Bundle of synaptic connections Winning neurons Input
  • 32. Biological Information Extraction Database Template Filling Data Analysis & Field Identification Data Classification & Field Extraction Information Extraction Field Property Identification & Learning Text Data DB Location Date DB Record

Notas do Editor

  1. Machine Learning ( 형주 ) >     - Supervised Learning, Unsupervised Learning 정의 >     - What if the data are (preprocessed) text documents?
  2. >     - Text Classification >     - Filtering >     - Extraction