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

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Does Deep network (e.g. # of hidden layer=2) always better than shallow network (i.e. # of hidden layer=1)?

I attempted to build a deep network (e.g. deep autoencoder) for some object classification, my result showed that the deep networks is worst than shallow network. However, from what I have read from ...
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5 views

Unreliable and uncertainty of RF prediction results (multiple runs) for my data set

Currently, I meet such questions when building Random Forest model using my data set. My full data set: X_lab: 839 * 469 and y_lab: 839 * 1 which is for all labelled data and X_unl: 20346 * 469 which ...
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5 views

Practical problem computing de k-nearest neighbors in CF?

I’m trying to apply de knn to a very dynamic system where users (like/dislike) items very frequently and new items became available all the time. My question is how often should the algorithm ...
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2answers
147 views

Evaluating features and similarity measures

I am currently developing a classificator, which is supposed to classify into a number of classes. For this purpose I am designing some features and similarity measures which I might use for a later ...
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1answer
25 views

Apriori Algorithm Support Calculation [on hold]

Why Apriori functions in arules library in R returns different values that what it should be? The sample data in the pic below. Each line between {} means that it is a single transaction. So ...
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12 views

Regarding Naive Bayes and conditional independence

We all have been talking about how Naive Bayes may, in some cases, not perform well due to the fact that this assumes conditional independence of features and MOSTLY, this is not true for real world ...
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1answer
55 views

SVM Classification with Duplicate Training Instances

I'm using SVMs with linear kernel for sentence classification (binary). My dataset contains many duplicate instances i.e. many sentences in the training set have identical feature vectors. In the ...
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23 views

What is the relationship between vector space models & support vector machines?

Is there a relation between them? Specifically, if I have a VSM can I classify it through SVM?
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152 views

Calculating the information gain on the features with python [on hold]

I'm looking for a python library that computes the information gain for the features given a training matrix. Are you aware of any?
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32 views

Stochastic Gradient Descent for Logistic Regression always returns a cost of Inf and weight vector never gets any closer

I am trying to implement a logistic regression solver in MATLAB and i am finding the weights by stochastic gradient descent. I am running into a problem where my data seems to produce an infinite ...
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19 views

Does Text Classification using SVM needs to use a dictionary to build the features vectors?

I'm kinda new to this, but I want to do an experiment I need your guys help. Open to all suggestions. Let's say I have around 5000 user accounts for which I only have several attributes [first name, ...
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2answers
58 views

Does the dataset size influence a machine learning algorithm?

So, imagine having access to sufficient data (millions of datapoints for training and testing) of sufficient quality. Please ignore concept drift for now and assume the data static and does not change ...
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15 views

Graphically, how does the non-linear activation function project the input onto the classification space?

I am finding a very hard time to visualize how the activation function actually manages to classify non-linearly separable training data sets. Why does the activation function (e.g tanh function) ...
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7 views

LIBSVM for pre-computed kernel and zero bias (b values is zero)

I want to do binary classification and I'm using LIBSVM library for that. I have a precomputed Kernel and my bias value (b) is zero. Can I do this in LIBSVM or do I have to use some other library? ...
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26 views

Visualize a large binary matrix with instances and three classes

I have a matrix with 9500 columns and 1000 rows. Each row represents an instance. I have three classes and an instance belongs to a class. Each column represents a binary feature. That is, each cell ...
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7 views

Meta-parameter search for elastic net regularization of general objective function

In their 2004 paper on elastic net regularization, Zou and Hastie present an efficient method for finding the meta-parameters by folding the $L_2$-regularization component into the OLS problem and ...
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1answer
40 views

What is the convex hull in ROC curve?

I'm reading a paper about ROC and PR curves. They mentioned the ROC convex hull but they don't define it or say what it is. Can someone please tell me the meaning of it? What is a convex hull in ROC ...
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2answers
115 views

Guideline to select the hyperparameters in Deep Learning

I'm looking for a paper that could help in giving a guideline on how to choose the hyperparameters of a deep architecture, like stacked auto-encoders or deep believe networks. There are a lot of ...
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11 views

algorithm to predict cost function

The goal of problem is to predict the weight for missing data . I have a dataset of categorical type as shown below ...
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25 views

What is the correct architecture for convolutional neural network?

I have seen several different architectures for convolutional neural network (CNN). I am confused which one is the standard and how do I decide what to use. I am not confused by the number of layers ...
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2answers
39 views

An intuitive meaning of the area under the PR curve?

Wikipedia says that an interpretation of the area under the ROC curve is: "the area under the curve is equal to the probability that a classifier will rank a randomly chosen positive instance higher ...
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1answer
23 views

How to apply the output layer function in a neural network

I am implementing a Neural Network in a somewhat different fashion. I train my neural network locally using a small subset, and export the weights. My goal is to test the neural network in a ...
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2answers
188 views

How to do exploratory data analysis to choose appropriate machine learning algorithm

We are studying machine learning via Machine Learning: A Probabilistic Perspective (Kevin Murphy). While the text explains the theoretical foundation of each algorithm, it rarely says in which case ...
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1answer
34 views

Different results from several “passes” of Random Forest on same dataset

I've been playing around with the German Credit dataset available in Kuhn & Johnson's caret package for ...
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1answer
73 views

k-means clustering on percentages

Can we do k-means clustering on percentage data (like 56%, 44%, 22%, 13%, etc.)? There is a data set, and data in various parts are measured in percentages.
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20 views

R programming, correlation of quantitave variables with one qualitative variable

I have a flat CSV file that has one column of student names, one column of grades (outcomes) coded as a factor A-F, and about 100 columns of test scores (independent variables) of various sorts, on ...
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12 views

Usage of libsvm with RBF kernel and no Offset

I'm using libsvm for the binary classification and using a precomputed Kernel. In my particular problem there is no bias term (it's zero). Is there anyway to adjust the bias term in libsvm (and not ...
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11 views

Why does Co-ordinate descent work? [on hold]

If it works does it mean that "function is convex if it's convex in any direction"?
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51 views

What're the differences between PCA and autoencoder?

Both PCA and autoencoder can do demension reduction, so what are the difference between them? In what situation I should use one over another?
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52 views

Prediction using Support Vector (SV) method in R

I came to know that using SVM method we can predict the future value more accurately than other normal methods (like ARIMA). My question is how do we give the future index value (let's say 101 when we ...
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2answers
90 views

Newbie to neural networks

Just starting to play around with Neural Networks for fun after playing with some basic linear regression. I am an English teacher so don't have a math background and trying to read a book on this ...
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2answers
135 views

Gaussian noise model derivation

I have the following linear regression model, $y = f(x;w) + n$, where $y$ is the vector of true labels, $x$ is the observed data, $f(x;w) = w^Tx$, and $n$ ~ $N(0, \sigma^2)$ is the noise. Why then ...
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1answer
193 views

Finding the projection used in multidimensional scaling

Background I have a set of data points in high-dimensional (512D) space that I wish to map to 2D for visualisation. I am interested in observing in 2D the (approximate) relative distances between the ...
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1answer
69 views

Detecting strong currents in a sparse directed graph

I have a very large, sparse, weighted, directed graph. The structure is such that it mainly consists of strings of nodes connected with highly weighted edges. These strings can be connected by weak ...
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39 views

The activities of the machine learning scientists at Amazon [on hold]

I'm looking for a job in machine learning and data mining and I came across Amazon Germany where they have offers as machine learning scientist. Well, I don't know if I fit for that since I'm a master ...
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17 views

Using standard machine learning tools on left-censored data

I'm developing a forecasting application whose purpose is to allow an importer to forecast demand for its products from its customer network of distributors. Sales figures are a pretty good proxy for ...
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3answers
110 views

Understanding Gaussian Basis function parameters to be used in linear regression

I'd like to apply the Gaussian basis function into a linear regression implementation. Unfortunately I'm having a hard time understanding a couple parameters in the basis function. Specifically mu ...
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2answers
25 views

What does “permutation invariant” mean?

I have seen a term "permutation invariant" version of the MNIST digit recognition task. What does it mean?
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1answer
38 views

I am having trouble understanding (and implementing) logistic regression for classifying into three classes

(For reference, i am using Kevin P Murphy's Book "Machine Learning: A Probabilistic Perspective" and implementing with MATLAN - without any toolboxes) I have a dataset with 392 samples (rows), each ...
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2answers
93 views

Recovering true data from multiple noisy versions

I am trying to find if there is any way to get the true data from multiple noisy versions, but the true data has a peculiar property. Problem Statement Consider a matrix $F=[f_1, f_2, ... , f_n]$ ...
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2answers
831 views

Are there any libraries available for CART-like methods using sparse predictors & responses?

I'm working with some large data sets using the gbm package in R. Both my predictor matrix and my response vector are pretty sparse (i.e. most entries are zero). I was hoping to build decision trees ...
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1answer
180 views

Choosing correct C and g parameters for libsvm

libsvm 3.18 Features: 10 I have used following, parameter range: ...
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1answer
261 views

Random forest on multi-level/hierarchical-structured data

I am quite new to machine learning, CART-techniques and the like, and I hope my naivete isn't too obvious. How does Random Forest handle multi-level/hierarchical data structures (for example when ...
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17 views

How to compute F-statistics for each features of regression models in glmnet?

I have learned lot's of Lasso regression models(20000) using glmnet. I need to compute somehow test statistics for each features of models. like F-statistics,... Can I do this using bootstrapping ? ...
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1answer
1k views

How do I use the GPML package for multi dimensional input?

I have downloaded the Gaussian Processes for Machine Learning (GPML) package (gpml-matlab-v3.1-2010-09-27.zip) from the website, and I can run the regression example (demoRegression) in Octave. It ...
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1answer
21 views

What does pre-training mean in deep autoencoder?

I am confused by the term "pre-training". What does it mean in deep autoencoder? And how does it help improving the performance of autoencoder? (I know this term comes from Hinton 2006's paper: ...
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1answer
92 views

What are the algorithms to detect bots clicking on a shortened URL?

I own a url shortening service. I want to deliver only legitimate statistics to my clients. There are possible scenarios that a particular user writes a script to automatically open the shortened URL, ...
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21 views

How to improve linear model generalization when autocorrelation is present?

I have features $X_t$ and response $Y_t$ (all continuous variables) and my objective is to find the best estimate of $f(X_t)=Y_t$ where $f$ is linear, and 'best' is defined as lowest generalisation ...
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2answers
87 views

Using decision trees to make a binary decision

I have a button that I can press or not press, a binary target that I would like to be 1 as often as possible, and a bunch of features. I also have a bunch of (feature, button choice, target) data, in ...
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156 views

Understanding the derivation of an equation in LDA modeling

When reading the derivation of LDA models, I usually get the following equations. I do not quite understand the second step, where $p(\mathbf{z}_{-i},\mathbf{w}|\alpha,\beta)$ was removed. Is that ...