Introduction to Information Retrieval SUPPORT VECTOR MACHINE Mainly based on https://nlp.stanford.edu/IR-book/pdf/15svm.pdf 1 Introduction to Information Retrieval Overview ▪ SVM is a huge topic ▪ Integration of MMDS, IIR, and Andrew Moore’s slides here ▪ Our foci: ▪ Geometric intuition ➔ Primal form ▪ Alternative interpretation from Empirical Risk Minimization point of view. ▪ Understand the […]
COMP9318: Data Warehousing and Data Mining Course Introduction What is Data Warehousing? •“A data warehouse is a subject-oriented, integrated, time-variant, and non-volatile collection of data in support of management’s decision-making process.” — W. H. Inmon •Data warehousing: • The process of constructing and using data warehouses •Difference between data warehouse and database 2 What is
COMP9318: Data Warehousing and Data Mining — L7: Classification and Prediction — Data Mining: Concepts and Techniques 1 n Problem definition and preliminaries Data Mining: Concepts and Techniques 2 ML Map Data Mining: Concepts and Techniques 3 Classification vs. Prediction n Classification: n predicts categorical class labels (discrete or nominal) n classifies data (constructs a
Final Examination Problem 1. Use the final-p1.csv dataset for this problem The given dataset has seven 2-dimensional objects and they are divided into two clusters. In the dataset, the first column is the object name, the second and the third columns are two attributes, and the last column shows the cluster of each object. Suppose
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Machine Learning and Data Mining in Business Lecture 2: Machine Learning Fundamentals Discipline of Business Analytics Copyright By PowCoder代写 加微信 powcoder Lecture 2: Machine Learning Fundamentals Learning objectives • Predictions and decisions. • Building blocks of learning algorithms. • Overfitting and the bias-variance trade-off. Basics of supervised learning Supervised learning • In supervised learning, we
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Machine Learning and Data Mining in Business Semester 1, 2022 Regression Project: Airbnb Pricing Analytics 1. Overview In this project your team will analyse data from Airbnb rentals in Sydney to provide market advice to hosts, real estate investors, and other stakeholders. Your team will have two tasks: the first will be to build a
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Classification (2) COMP9417 Machine Learning and Data Mining Term 2, 2021 COMP9417 ML & DM Classification (2) Term 2, 2021 1 / 71 Acknowledgements Material derived from slides for the book “Elements of Statistical Learning (2nd Ed.)” by T. Hastie, R. Tibshirani & J. Friedman. Springer (2009) http://statweb.stanford.edu/~tibs/ElemStatLearn/ Material derived from slides for the book
Tree Learning COMP9417 Machine Learning and Data Mining Term 2, 2021 COMP9417 ML & DM Tree Learning Term 2, 2021 1 / 67 Acknowledgements Material derived from slides for the book “Machine Learning” by T. Mitchell McGraw-Hill (1997) http://www-2.cs.cmu.edu/~tom/mlbook.html Material derived from slides by Andrew W. Moore http:www.cs.cmu.edu/~awm/tutorials Material derived from slides by Eibe Frank
Classification (1) COMP9417 Machine Learning and Data Mining Term 2, 2021 COMP9417 ML & DM Classification (1) Term 2, 2021 1 / 86 Acknowledgements Material derived from slides for the book “Elements of Statistical Learning (2nd Ed.)” by T. Hastie, R. Tibshirani & J. Friedman. Springer (2009) http://statweb.stanford.edu/~tibs/ElemStatLearn/ Material derived from slides for the book
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Ensemble Learning COMP9417 Machine Learning and Data Mining Term 2, 2021 COMP9417 ML & DM Ensemble Learning Term 2, 2021 1 / 51 Acknowledgements Material derived from slides for the book “Elements of Statistical Learning (2nd Ed.)” by T. Hastie, R. Tibshirani & J. Friedman. Springer (2009) http://statweb.stanford.edu/~tibs/ElemStatLearn/ Material derived from slides for the book