data mining

MAST90083 Computational Statistics & Data Mining Bootstrap and SVM Practical 10: Bootstrap and Support Vector Machines This practical covers � the use of the bootstrap R package, boot and � the use of the support vector machines R package, e1071. Question 1: Bootstrap The table below gives 13 measurements of corrosion loss (yi) in copper-nickel […]

MAST90083 Computational Statistics & Data Mining Bootstrap Methods Tutorial & Practical 8: Bootstrap Methods Question 1 In this question we explore the bias reduction performance of a bootstrap estimator of a third power of the mean of a population assumed to be a scalar θ0 = θ(F0) = µ 3 where µ = ∫ xdF0(x)

MAST90083 Computational Statistics & Data Mining SDG & LR Tutorial & Practical 2: Synthetic Dataset Generation (SDG) and Linear Regression (LR) In this practical, our aim is to learn how to use the least square estimator to solve a linear regression problem of the type Y = DA + E where Y ∈ RN×V is

MAST90083 Computational Statistics & Data Mining SVM and ANNs Tutorial & Practical 11: Solutions Question 1 1. The kernel density estimator has the form p (x) = 1 N N∑ i=1 1 hp k (x, xi) where hp is the normalization constant for the kernel. Using the above we have p (x|t) = 1 N+

MAST90083 Computational Statistics & Data Mining KR and GAM Figure 1: Solution of Question 1 rm( l i s t=l s ( ) ) # c l e a r a l l the v a r i a b l e s in conso l e l i b r a r y (

MAST90083 Computational Statistics & Data Mining Linear Regression Tutorial & Practical 3: Ridge Regression Question 1 Given the model y = Xβ + � where y ∈ Rn, X ∈ Rn×p is of rank r ≤ p < n and � ∈ Rn ∼ N (0, σ2In). Let β̂ be the estimate of β obtained

CORPFIN 2503 – Business Data Analytics 2021 S2, Workshop 2: Visual analytics and data mining £ius 1 Time series stock market data Let’s download time series stock market data for all stocks traded on ASX using Eikon: 1. Search for Screener 2. Filter for stocks traded in Australia (country of exchange) 3. Click button `Launch