presentation
1 Machine Learning Learning from Observations. 2 2 What is Learning? Herbert Simon: Learning is any process by which a system improves performance from.
Lirong Xia Naïve Bayes Classifiers Friday, April 8, 2014.
DRAFT 1 Developing and Implementing a Monitoring & Evaluation Plan.
Chad Allison May 2013 1-2 Formal Classroom Evaluations Drop-in Visits.
Computer Science CPSC 502 Lecture 15 Machine Learning: Intro and Supervised Classification.
Project Monitoring and Evaluation
Introduction to Mathematical Modeling in Mathematica
Automated Screening Malaria Parasite Using Light Microscopic Images
Lirong Xia Perceptrons Friday, April 11, 2014. Classification –Given inputs x, predict labels (classes) y Examples –Spam detection. input: documents;
IMBALANCED DATA David Kauchak CS 451 – Fall 2013.
Machine Learning Up until now: how to reason in a model and how to make optimal decisions Machine learning: how to acquire a model on the basis of.