EGB345 Control and Dynamic Systems JJF/15 COMPUTER LAB 2 – MODELLING AND CHECKING YOUR ANSWERS You will need to demonstrate some of skills developed in this computer lab in your pre-lab submission. Task 1: You are told that a vehicle with suspension has transfer function: where R(s)corresponds to the road surface and X s (s)is […]
程序代写代做代考 matlab EGB345 Control and Dynamic Systems JJF/15 Read More »
Microsoft Word – COMP3308-assignment2-2018-final.docx COMP3308 – Introduction to Artificial Intelligence Semester 1, 2018 Page 1 of 7 Assignment 2: Classification Deadlines Submission: 5pm, Friday 18th May, 2018 (week 10) This assignment is worth 20% of your final mark. Task description In this assignment you will implement the K‐Nearest Neighbour and Naïve Bayes algorithms and evaluate them on a real dataset using the stratified cross validation method. You will also evaluate the performance of other classifiers on the same dataset using Weka. Finally, you will investigate the effect of feature selection, in particular the Correlation‐based Feature Selection method (CFS) from Weka. Late submissions policy No late submissions are allowed. Programming languages Your implementation can be written in Python, Java, C, C++ or MATLAB. The assignment will be tested on the University machines, so your code must be compatible with the language version installed on those machines. You are not allowed to use any of the built‐in classification libraries for the purposes of this assignment. Submission and pair work Your assignment can be completed individually or in pairs. See the submission details section for more information about how to submit. This assignment will be submitted
PTRL5014 Take-home Assignment General Information This assignment consists of two parts, each requiring a separate submission. Part 1 submission is a single word file, while in part 2, you must combine all matlab files and the word file (containing the figures) into a zip file and upload that. The assignment is marked out of 100
程序代写代做代考 case study database matlab PTRL5014 Take-home Assignment Read More »
Data Representation for High Dimensional Data Lecture 6: Dimensionality Reduction 1 CMSC5741 Big Data Tech. & Apps. Prof. Michael R. Lyu Computer Science & Engineering Dept. The Chinese University of Hong Kong A Compression Example 2 Outline Motivation SVD CUR Application of SVD and CUR PCA Extension to robust PCA 3 Dimensionality Reduction Motivation Assumption:
EECS 391 Introduction to Artificial Intelligence Fall 2018, Written Assignment 5 (“W5”) Due: Tue Nov 27. Submit a single pdf document along with your code for the whole assignment to Canvas before class. You may scan a handwritten page for the written portions, but make sure you submit a single pdf file. Total Points: 100
程序代写代做代考 python algorithm matlab EECS 391 Introduction to Artificial Intelligence Read More »
COMP3308 – Introduction to Artificial Intelligence Semester 1, 2018 Page 1 of 4 Assignment 1: Search Methods Deadline Submission: 5pm, Friday 20 April, 2018 (week 6). This assignment is worth 10% of your final mark. It is an individual assignment; no group work. Late submissions policy No late submissions are allowed. Programming languages Your implementation
Springer Texts in Statistics An Introduction to Statistical Learning Gareth James Daniela Witten Trevor Hastie Robert Tibshirani with Applications in R Springer Texts in Statistics Series Editors: G. Casella S. Fienberg I. Olkin For further volumes: http://www.springer.com/series/417 http://www.springer.com/series/417 Gareth James • Daniela Witten • Trevor Hastie Robert Tibshirani An Introduction to Statistical Learning with Applications
bayesGauss.dvi Conjugate Bayesian analysis of the Gaussian distribution Kevin P. Murphy∗ murphyk@cs.ubc.ca Last updated October 3, 2007 1 Introduction The Gaussian or normal distribution is one of the most widely used in statistics. Estimating its parameters using Bayesian inference and conjugate priors is also widely used. The use of conjugate priors allows all the results
程序代写代做代考 Bioinformatics flex Bayesian matlab bayesGauss.dvi Read More »
COMP9334 Project, Session 1, 2018: Server setup in data centres Version 1.1 Due Date: 11:00pm Sunday 20 May 2018. This version: 22 April 2018 Updates to the project, including any corrections and clarifications, will be posted on the subject website. Make sure that you check the course website regularly for updates. Change log Note: New
程序代写代做代考 python Java matlab chain COMP9334 Project, Session 1, 2018: Read More »
QBUS6850: Tutorial 2 – Linear Algebra, Data Handling and Plotting Objectives To handle data using Numpy, Pandas libraries; To plot data using matplotlib library; 1. Libraries For this tutorial you will need to use external libraries. Libraries are groups of useful functions for a particular domain. The import statement is used to import