Classification, Clustering and Bayes…

Slides:

Advertisements

Similar presentations

1 Peter Fox Data Analytics – ITWS-4963/ITWS-6965 Week 7a, March 10, 2015 Labs: more data, models, prediction, deciding with trees.

Advertisements

1 Peter Fox Data Analytics – ITWS-4963/ITWS-6965 Week 3b, February 7, 2014 Lab exercises: datasets and data infrastructure.

Today’s Topic Language of web page - HTML (Hypertext Markup Language)

Auctions – Lecture 2 Nancy S. Bazar February 25, 2003.

1 Peter Fox Data Analytics – ITWS-4963/ITWS-6965 Week 2b, February 6, 2015 Lab exercises: beginning to work with data: filtering, distributions, populations,

HTML. WHAT IS HTML HTML stands for Hyper Text Markup Language HTML is not a programming language, it is a markup language A markup language is a set of.

1 Peter Fox Data Analytics – ITWS-4963/ITWS-6965 Week 4b, February 14, 2014 Lab exercises: regression, kNN and K-means.

1 Peter Fox Data Analytics – ITWS-4963/ITWS-6965 Week 4b, February 20, 2015 Lab: regression, kNN and K- means results, interpreting and evaluating models.

Win32 Programming Lesson 2: The Tools of the Trade.

The Romeo and Juliet Radio Drama. Your Programming Guide During this lesson, your group will complete the following tasks. Click each one in turn to work.

SEC835 Security in Databases and Web applications Presentation.

WEEK 1 You have 10 seconds to name…

1 Peter Fox Data Analytics – ITWS-4963/ITWS-6965 Week 5b, February 21, 2014 Interpreting regression, kNN and K-means results, evaluating models.

1 Peter Fox Data Analytics – ITWS-4600/ITWS-6600 Week 2b, February 5, 2016 Lab exercises: beginning to work with data: filtering, distributions, populations,

© 2008 General Parts International, Inc. Written permission is required to copy or forward to anyone other than the intended recipient. TeammateTime Corporate.

1 Peter Fox Data Analytics – ITWS-4600/ITWS-6600 Week 3b, February 12, 2016 Lab exercises /assignment 2.

Poetry Portfolio Spring, Include in your Poetry Portfolio: At least 5-10 poems on a variety of topics in a variety of styles. –At least one free.

1 Peter Fox Data Analytics – ITWS-4600/ITWS-6600 Week 12b, April 22, 2016 Cross-validation and Local Regression Lab.

RDG 410 Week 2 Individual Assignment Phonics Competency Assessment Resource: University Material: Phonics Competency Pretest. Complete the Phonics Competency.

XBIS 219 Week 6 Assignment Club IT, Part 2 Write a 700- to 1050-word paper in APA format using the information gathered from your review of the Club IT.

BIS 303 Week 3 Learning Team Hospitality Information Systems Third Party Reservation Options Resource: Hospitality Information Systems: Third Party Reservation.

Tips for Efficient Air Conditioning Maintenance

Introduction to Data Analytics, Current Challenges. Course Outline

Data Analytics – ITWS-4963/ITWS-6965

Peter Fox and Greg Hughes Data Analytics – ITWS-4600/ITWS-6600

Data Analytics – ITWS-4600/ITWS-6600

Group 1 Lab 2 exercises /assignment 2

Classification, Clustering and Bayes…

Data Analytics – ITWS-4963/ITWS-6965

ASSIGNMENT NO.-2.

The UK Tier 1 Entrepreneur Visa and the UK Representative of Overseas Business Visa - SmartMove2UK

TO DO LIST: Take a look at your Writing Checklist in your research packet. Look at the information in your packet about the format, length and other requirements.

February 12 – 19, 2018.

Labs: Dimension Reduction, Factor Analysis

Labs: Dimension Reduction, Factor Analysis

Google Analytics.

Data Analytics – ITWS-4600/ITWS-6600/MATP-4450

Data Analytics – ITWS-4600/ITWS-6600/MATP-4450

Group 1 Lab 2 exercises and Assignment 2

Data Analytics – ITWS-4600/ITWS-6600/MATP-4450

Weighted kNN, clustering, “early” trees and Bayesian

Web Site Analysis By:.

Cross-validation and Local Regression Lab

Kapi’olani Community College

Peter Fox Data Science – ITWS/CSCI/ERTH 4350/6350 Module 2, Fall 2017

Assignment 2 (in lab) Peter Fox and Greg Hughes

Local Regression, LDA, and Mixed Model Lab

ITWS-4600/ITWS-6600/MATP-4450/CSCI-4960

Labs: Trees, Dimension Reduction, Multi-dimensional Scaling, SVM

Lab weighted kNN, decision trees, random forest (“cross-validation” built in – more labs on it later in the course) Peter Fox and Greg Hughes Data Analytics.

ITWS-4600/ITWS-6600/MATP-4450/CSCI-4960

Cross-validation Brenda Thomson/ Peter Fox Data Analytics

Bell Work Set up a Cornell Note.

Peter Fox Data Science – ITWS/CSCI/ERTH 4350/6350 Module 3, Fall 2017

Cross-validation and Local Regression Lab

Cross-validation and Local Regression Lab

Classification, Clustering and Bayes…

Local Regression, LDA, and Mixed Model Lab

COT 5611 Operating Systems Design Principles Spring 2012

Art 222 Digital Multimedia In-class Presentation Week 14B

Assignment 1: Classification by K Nearest Neighbors (KNN) technique

Data Analytics – ITWS-4600/ITWS-6600/MATP-4450

ITWS-4600/ITWS-6600/MATP-4450/CSCI-4960

Tips to Improve Conversion Rate Optimization. What Is Conversion Rate? For the uninitiated, the conversion rate of a website is the percentage of visitors.

Group 1 Lab 2 exercises and Assignment 2

Theory and Practice of Web Pedagogies 2/03/2004

SPED 300 Assignments due Week 3

Analytics Tips and Tricks

Presentation transcript:

Classification, Clustering and Bayes… Peter Fox Data Analytics – ITWS-4600/ITWS-6600/MATP-4450 Group 2 Lab 2, February 15, 2018

Assignments to come Term project (A6). Due – end of term. 30% (25% written, 5% oral; individual). Available before spring break. Assignment 7: Predictive and Prescriptive Analytics. Due ~ week ~ 12. 15% (written; individual); Assignment 5: presentations will be the week before spring break (formats to be discussed…)

Plot tools/ tips More script fragments on the web site (aquarius.tw.rpi.edu/html/DA ) also continue labs from week 4 and 5 as well as those here… Default naiveBayes is library(e1071) Tip: Resetting plot space: par(mfrow=c(1,1)) par()$mar # to view margins par(mai=c(0.1,0.1,0.1,0.1)) Assignment 4 and 5 on LMS

Do over… Make sure that you get to the “bronx” dataset and group2/lab1_bronx1.R and lab1_bronx2.R script fragments You need it for A4!!

Today on web under group2/ lab2_abalone.R lab2_kknn1.R lab2_nbayes1.R lab2_nbayes2.R lab2_nbayes3.R lab2_nbayes4.R lab2_swiss.R