Methods and principles of building "computer systems that automatically improve with experience."

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Estimating the covariance matrix in LDA

I was trying to derive the equations from page 109 in "elements of statistical learning" (image below) To be honest, I am not sure how the covariance $\Sigma$ is estimated (the third bullet point in ...
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1answer
119 views

Gaussian Process Kernel and Ridge Regression

Can a Dual Ridge Regression produce the same prediction results as a Gaussian Process with a polynomial kernel $K(x,x')=(x^Tx'+1)^2$ in less time complexity (GP is $O(n^3)$ ) using Cholesky ...
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13 views

Imbalanced values in the feature set of training and testing samples in SVM (Multi class classification)

Currently I only know about the imbalanced in the structure of data set (e.g. too many positive samples, few negative samples..). But how about imbalanced in the value of features in each samples? For ...
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1answer
63 views

SVM primal formulation: does the constants constraint matter?

When finding the maximum margin separator in the primal form we have the quadratic program $$min\frac{1}{2}||\theta||^2$$ $$\text{ subject to: } y^{(t)}(\theta \cdot x^{(t)} + \theta_0) \geq 1, \ ...
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15 views

Why even my training data failed during the prediction of libsvm [duplicate]

Currently I'm using libsvm for my one class classification problem. I have 10 samples in my training set, 5 samples in my testing set, both of my training and testing set is scaled by svm_scale, then ...
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19 views

Classifier jars for java

I have a train file which has categorical features like IN JJ PRP_VBP VB NN PRP$ . . . The third column is the ground truth and can have value only out of ...
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35 views

Neural Network, dependence among outputs?

Is there a way to train a neural network in the following manner: You have $n$ observations in the training set. The neural net will start with random weights, and produce $n$ outputs. I want to ...
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1answer
121 views

How to design neural networks for pattern recognition in biometry?

Having read numerous texts regarding neural networks and their characteristics, I am getting increasingly confused, paradoxically – I am looking for a brief explanation or references to the right ...
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1answer
62 views

How to define train and test sets in financial time series for estimating machine learning parameters

After reading some material, I found few options for defining train and test sets: Just splitting with no change. Accumulating/moving window of train set. Leave a relatively small (warming) period ...
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1answer
84 views

What is SVM regression? Is it for regression or classification?

I'm trying to understand what is SVM regression. It's used for classification or regression? Can someone give an intuitive understanding of it?
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28 views

Best Methods for data-mining neuroimaging data with 1000 subjects

I am part of a team tasked with performing exploratory analysis of a large data set containing neuro-imaging scans. For each scan I will likely calculate some variable that relates to brain function - ...
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25 views

Significance test for multiclass classifier

In a multiclass classification problem, I want to measure the significance of my classifier against the null hypothesis (in this case, chance level). In this paper, in section 3.4, for a binary ...
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20 views

What do I call a set of datasets

For training a Machine learning model, I have 3 datasets: Training Validation Testing Normally I obtain there by dividing up the full dataset into pieces. I've created a function in my code to ...
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14 views

Choosing the values of a proper subset of features to maximise regression tree output

Suppose I have a regression tree and feature set $X$. Suppose that the feature set is composed of $X:=\{X_0,X_1,...,X_{100}\}$, where each $X_i \sim N(0,\sigma^2)$. Suppose that ...
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1answer
41 views

Dimension of weight vectors in SVMs

For a given set of features (say with dimension a) and for a given set of labels (say m labels), how to relate the given features with the weight vector of the SVM in general? Will it be equal to ...
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3answers
132 views

Multiple Regression and number of parameters to include for a learning algorithm

I am quite new to Machine Learning and come from a computing background. I have a quite big set of features (~50) with about 4k observations. Is it correct thinking to include all of them in a ...
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2answers
76 views

What's the difference between kernel and stepwise logistic regression?

I am confused by different terms of logistic regression. What are the differences between stepwise, kernel, forward, and backward?
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41 views

Exploratory Analysis - finding the most important factor

I have a dataset of 113 variables. In exploratory analysis the first thing I want to know is what are the most important factors on a single variable (revenue). I learned that naive Bayes would ...
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1answer
45 views

Clustering algorithms assigning probability values

I have a distance matrix for some data I want to cluster. However, I don't just want to assign elements to clusters, but I also want to assign a probability for each element to belong to each cluster. ...
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1answer
61 views

building a classification model for strictly binary data

i have a data set that is strictly binary. each variable's set of values is in the domain: true, false. the "special" property of this data set is that an overwhelming majority of the values are ...
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1answer
64 views

Is it abnormal that out-of-sample fit is better than in-sample?

I'm using Eureqa, as machine learning tool to fit a formula to my data. I found out that the formula fits my test data better than my training data! Is this abnormal?
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1answer
150 views

'Uniformization'?

I am looking for a better term for what I call 'uniformification', where I change data to make it more close to uniformly distributed. I am doing a project in which I try to make the output of a ...
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0answers
17 views

How to estimate False Discovery Rate from p-value distribution?

I have learned many models and I calculated p-values for the cross-validation errors. I want to select significant models based on the false discovery rate (FDR). How can I estimate the FDR from ...
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28 views

Constructing a covariance matrix and finding first principal component

So far in the topic of principal component analysis, I seem to be jumping around in understanding these various topics, and have a few questions that I need to help solidify my overall understanding. ...
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1answer
18 views

highly sporadic validation error during training with multilayer perceptron

I'm encountering an issue where a classifier I'm developing reports validation errors during training that span a wide range of values without consistently decreasing over time. Unfortunately, I'm new ...
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29 views

Random forest: confounding factors

I have N variables in K samples. There is a classification variable, T (treatment), and a confounding variable -- sex. Unfortunately, in the "no treatment" (CTRL) group there are significantly more ...
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27 views

How to reduce the dimension of a test data and make it uncorrelated?

I am working on classification of 16000 cell images. Each of them consists of 706 features related to intensity, morphology, colocalisation and texture of the cell. The train set consists of 11 ...
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1answer
52 views

How is AUC of decision tree calculated?

I have a dataset which only has one continuous variable, and I try to use decision tree algorithm to build a model which classify the +ve and -ve label from the dataset. I run 10-fold ...
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16 views

Multivariate Gaussian v. PCA + Independent Gaussians for Anomaly Detection

In Andrew Ng's Machine Learning Coursera Class, he covers anomaly detection in multiple dimensions for both independent univariate Gaussians and multivariate Gaussians, the latter being more costly ...
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1answer
132 views

Bayesian MLPs using the MCMC methods - any tricks of the trade?

Having used the NETLAB library for MATLAB to implement Bayesian Multi-Layer Perceptron (MLP) neural networks using MacKay's evidence framework, I am now experimenting with Markov Chain Monte Carlo ...
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1answer
38 views

How to initiate bias node in a restricted Boltzman machine

I am new to Neural Networks and trying to implement RBM. I am stuck on initializing the visible layer's bias value. Is it supposed to initialize to some random number or there is some probabilistic ...
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35 views

Supervised or unsupervised learning problem?

currently I'm working a pattern recognition problem. I have been using supervised learning (neural network and svm with one class classification) but I think I'm doing it in a wrong way. For ...
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1answer
24 views

Supervised learning based on phase space representation

Phase space learning Paper1 and Paper2 in neural network represents the input in higher dimension in auto associative learning. So, the network functions as an auto-associative memory where dynamical ...
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32 views

Sizing of training and validation sets in machine learning: Is there a proven optimum, or merely heuristics?

When I watch presentations where machine learning algorithms were used, the amount of data put in the training and validation sets seems to be somewhat arbitrary. Sometimes it's 80-20, sometimes it's ...
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1answer
27 views

Using LDA in non-realtime twitter data

I try to understand user characterization from twitter data. How can I understand the user's interest from statuses? From my researches, LDA(Latent Dirichlet Allocation)suitable for topic extraction. ...
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14 views

Reference Request: Human speech extraction using Machine Learning

I am trying to extract human voice from a noisy clip and studied some test upon it like, voice clipping using deep learning or MLP ann etc., then speech identification using a sequence based ...
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19 views

Segmenting an interval sensibly

Is there a canonical/recommended approach to or algorithm for splitting up an interval with the intent of minimizing the number of segments while keeping a high accuracy? It is essentially an ...
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18 views

Need subspace partition algorithm, not necessarily a full classifier

The image above represents a hypothetical data set of interest. For some set of points in N-dimensional space (each attribute of the data set corresponds to one dimension), I want to identify ...
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1answer
23 views

Statistic test on percentage correct classified by emotion recognition

For a potential emotion recognition bachelor-project I was wondering what statistical test I have to perform when I get my results to test whether it's significant. I will be testing which combination ...
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16 views

Low accuracy for training in image classification

I'm a newbie using LinearSVM to train the classifier. I labelled the images of 'buildings' as 1 and the others as -1. The training result is as follows : and As you can see in the image some of ...
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26 views

Possible classification techniques to use when each feature is a probability distribution

I am working with some data where the features have a temporal aspect (e.g. how often does a feature occur between $t_{begin}$ and $t_{end}$). I am trying to build a binary classifier for this data. ...
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1answer
72 views

Good algorithms for feature extraction from images?

I am searching for some algorithms for feature extraction from images which I want to classify using machine learning . I have heard only about [scale-invariant feature transform][1] (SIFT), I have ...
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1answer
48 views

When to use accuracy and precision to evaluate binary classifiers?

I came a cross two ways to evaluate the performance of binary classifiers: accuracy and precision. When to choose each? And what are the advantages and disadvantages of each one?
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1answer
58 views

Deriving $\beta$ from expected loss function (Hastie, Tibshirani)

I am looking at equation (2.16) from Elements of Statistical Learning and can't seem to be able to derive it. I used $f(x) = x^T\beta$ as the linear model, and tried calculating $\beta$ by minimizing ...
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3answers
190 views

Evaluating a regression model

For classification problems I have been using Neural Networks and measuring Type I and II error using the confusion matrix and its measures as per this resource which is pretty straight forward. ...
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1answer
85 views

Run time analysis of the clustering algorithm (k-means)

I was reading some notes on ML and clustering and it claimed that the run time of clustering was O(kn) where k is the number of clusters and n is the number of points. I was wondering why this was ...
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24 views

Statistical testing: Multiple classifiers, 1 domain. Would rANOVA be appropriate?

When comparing the performance of two classifiers over a single domain, in the context of a classification problem in machine learning, it is common to use a paired t-test, using the 10 average ...
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1answer
103 views

Orthogonality in bias variance tradeoff

I have a function class $\mathcal{F}$. I get $n$ samples according to a model $$y = f^*(x)+\epsilon$$ I find the best $\hat{f}$ from these training samples i.e. $$\hat{f} = \arg\min\limits_{f\in ...
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4answers
529 views

Hints on this computer vision / machine learning problem

I've been working for a while on a pet problem. The task is to identify and segment out the dark lines and possibly the wiggly ones too. I'm not looking for anyone to solve this problem for me...I'm ...
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44 views

How to perform hypothesis testing for comparing different classifiers

I am trying to classify a small dataset (around 500 records) into two classes. I used various methods like SVM, Naive Bayes and k-nn classifier. Now, I would like to set the results from one of the ...