Machine Learning Homework 1
Ayush Jaiswal
USC ID: 4487908418
University of Southern California
1
1.1
Naive Bayes
Parametric form of Naive Bayes with Gaussian Assumption
We use the notation Y = y0 for Y = 0 and Y = y1 for Y = 1. We know from the problem de

CSCI567 Fall 2016
1
Homework #1
Due 09/21/16 23:59 PDT
Density Estimation
(a) (10 points) Suppose we have N i.i.d samples x1 , x2 , , xn . We will practice the maximum
likelihood estimation techniques to estimate the parameters in each of the following ca

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
October 12, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
October 12, 2016
1 / 41
Pragmatics in Classification
Outline
1
Pragmatics in Classification
Dr. Yan Li

CSCI567 Fall 2015
Homework #2 Solution
Problem 1: Logistic Regression
a) The the negative log likelihood is
n
Y
L(w) = log( P (Y = yi |X = xi )
i=1
=
=
n
X
log(P (Y = yi |X = xi )
(1)
i=1
n
X
(yi log(wT xi ) + (1 yi ) log(1 (wT xi )
i=1
b) The first deriv

CSCI 567 Discussion: Week 4
Sungyong Seo, Keyvan Moghadam
University of Southern California
September 23, 2016
Sungyong Seo, Keyvan Moghadam (usc)
CSCI 567 Discussion#4
September 23, 2016
1 / 11
Basic Information
1
We have an office hour 5:00pm to 5:50pm

CSCI 567 Discussion: Week 3
Sungyong Seo, Keyvan Moghadam
University of Southern California
September 16, 2016
Sungyong Seo, Keyvan Moghadam (usc)
CSCI 567 Discussion#3
September 16, 2016
1 / 15
Basic Information
1
We have an office 5:00pm to 5:50pm every

CSCI 567: Mini-Project
Fall 2016
2016 BYTECUP Challenge
1
Introduction
In the mini-project, you will have the chance to explore an interesting machine learning problem by
participating in the 2016 BYTECUP Challenge, which is being organized by IEEE China

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
October 31, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
October 31, 2016
1 / 26
Tips for Mini-project
Outline
1
Tips for Mini-project
2
Dimensionality reducti

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
November 2, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
November 2, 2016
1 / 29
Introduction to Hidden Markov Model
Outline
1
Introduction to Hidden Markov Mo

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
October 12, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
October 12, 2016
1 / 41
Pragmatics in Classification
Outline
1
Pragmatics in Classification
Dr. Yan Li

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
September 26, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
September 26, 2016
1 / 15
Generative versus discriminative
Outline
1
Generative versus discriminativ

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
November 14, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
November 14, 2016
1 / 28
Review of Classes
Outline
1
Review of Classes
2
Sample Questions
Dr. Yan Liu

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
September 26, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
September 26, 2016
1 / 27
Linear regression
Outline
1
Linear regression
Motivation
Algorithm
Univari

Sample Quiz#1
Machine Learning
CSCI 567 Fall 2016
1
Short Questions
In the quiz, there are 8-9 short questions. The following are 3 sample short questions.
1.1
Basic Concepts
(a) (2 points) Given a training dataset cfw_(xn , yn )N
n=1 , where yn are label

Maximum Likelihood, Logistic Regression,
and Stochastic Gradient Training
Charles Elkan
[email protected]
January 10, 2014
1
Principle of maximum likelihood
Consider a family of probability distributions defined by a set of parameters .
The distributions

CSCI567 Fall 2016
1
Homework #3
Due 10/19
Bias Variance Trade-off (10 Points)
Consider a dataset with n data points (xi , yi ), xi Rp1 , drawn from the following linear model:
y = x> ? + ,
where is a Gaussian noise and the star sign is used to differentia

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
October 17, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
October 17, 2016
1 / 34
Clustering
Outline
1
Clustering
K-means clustering
Gaussian mixture models
EM

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
September 7, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
September 7, 2016
1 / 44
First Classifier : Nearest neighbor classifier
Outline
1
First Classifier :

CSCI567 Machine Learning (Fall 2016)
Dr. Yan Liu
[email protected]
August 28, 2016
Dr. Yan Liu ([email protected])
CSCI567 Machine Learning (Fall 2016)
August 28, 2016
1 / 31
About this Course
Outline
1
About this Course
Administration
Syllabus
2
Overview