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

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Interpretation of Linear SVM Coefficients [duplicate]

I’m building a model using Linear SVM from the Scikit-learn package in Python. I have found that Linear SVM performs much better on my training set than Logistic Regression. My question is, is there ...
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1answer
36 views

Meaning of latent features?

I'm trying to understand matrix factorization models for recommender systems and I always read 'latent features', but what does that mean? I know what a feature means for a training dataset but I'm ...
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4answers
103 views

Analysing a CV with machine learning

What would you use to categorise or rank a Resume/CV with machine learning? I would like to make particular CVs stand out to recruiters.
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14 views

A framework for comparing the performance of Expectation Maximization

I have my own implementation of the Expectation Maximization (EM) algorithm based on the following paper http://pdf.aminer.org/000/221/588/fuzzy_k_means_clustering_with_crisp_regions.pdf I would like ...
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9 views

Which classifier is the best for short text classification, Naive Bays or RBFN? [closed]

I am doing my M.E. project on short text classification for Online Social Networks.I am using Weka for classification.Please tell me between Naive Bays and RBFN which classifier is the good one for ...
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11 views

Naive Bays classifier showing results for precision, recall and F value is always 1

I am implementing Naive Bays text classifier using Weka. I have trained it with very few words (about 20). I am getting the result that precision, recall and f value all as 1. Is this possible? ...
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1answer
62 views

What data mining/machine learning approach to use for a scoring model?

Suppose I have a large data set with lots of features(attributes). And I'm tasked to build some kind of scoring model to rank certain objects with all these features. How do I go about doing this? ...
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20 views

Method to select meaningful features for nearest neighbor classification

i try to perform some k nearest neighbor classification in R. That for i want to select the most meaningful features to deal with the curse of dimensionality. I have already decided to use Mahalanobis ...
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3answers
51 views

Recognition of simple patterns and prediction

I have been doing supervised learning and classification with multilayer perceptron for some time. But now I need to use unsupervised learning to infer the presence of a pattern and I would need some ...
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25 views

Squared Error vs Absolute Error loss functions [duplicate]

The two most popular types of loss functions are 1) squared error: $L(y,f(x))=(y-f(x))^2$ --> best estimate is the $E(Y|x) $ 2) absolute error: $L(y,f(x))=|y-f(x)|$ --> best estimate is the ...
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1answer
49 views

How to compare models from different but related datasets?

I'm building regression models on four the different but related data set and at the end, I want to test the significance of models. Since my models are built in a different data set, it's not ...
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53 views

Mixture of probits: understanding truncated-based likelihoods

I am trying to implement a mixture model of probits to infer the best decision boundary for every latent subpopulation. When doing Gibbs sampling, we eventually have to compute $P(y^* | w_c)$ where ...
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1answer
18 views

Regression Gaussian Estimates instead of points

I am using a support vector regression is order to get estimates of a variable y. I want to receive a probability distribution of my estimates and not just point estimates. I want to predict Gaussian ...
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1answer
38 views

When is it appropriate to use PCA as a preprocessing step?

I understand that PCA is used for dimensionality reduction to be able to plot datasets in 2D or 3D. But I have also seen people applying PCA as a preprocessing step in classification scenarios where ...
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0answers
13 views

After applying SVD, how do I find which features from my original dataset were most significant?

I'm using MathNet.Numerics library in C# to find the SVD but the Sigma matrix gives no indication of which values correspond to which features. It simply lists them in the most significant order. ...
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27 views

Calculating the variance of a model?

I often hear about the bias-variance tradeoff to evaluate classifiers. Now I want to calculate them. I often compute the AUC of a binary classifier to evaluate its performance and do a 10-fold ...
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0answers
37 views

Some doubt in reading Machine Learning A Probabilistic Perspective ( chapter 3.2 )

When I am reading Murphy's Machine Learning A Probabilistic Perspective. In chapter 3.2. I have some doubt. I think the author want to express is two things. First, we can use Bayes formula to ...
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1answer
76 views

What is the difference between a multi-label and a multi-class classification?

What is the difference between multi-label classification and multiclass classfication. Speficially, what is the difference between a label and a class? Please provide a clear example. "Multiclass ...
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25 views

Usefulness of Z-normalization in Machine Learning

Z-normalization means rescaling the feature $X$ by subtracting the average $\mu$ and dividing by its standard deviation $\sigma$, i.e., $(X-\mu)/\sigma$. What is the usefulness of normalizing data ...
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21 views

Binary classification of dated text documents with seasonality

I have a collection of training documents with publication dates, where each document is labeled as belonging (or not) to some topic T. I want to train a model that will predict for a new document ...
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3answers
319 views

How is cross validation different from data snooping?

I just finished "An Introduction to Statistical Learning". I wondered whether using cross-validation to find the best tuning parameters for various machine learning techniques is different from data ...
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1answer
67 views

Analysis of Customer satisfaction surveys

I have customer feedback data about 2-3 products from 100 customers. Number of questions are around 160. I have data in excel format. Header row contains the question and row below contains the ...
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0answers
52 views

Rademacher bounds for unbounded loss functions

All common treatment of PAC bounds based on Rademacher complexity assume a bounded loss function (for a self-contained treatemnt, see this handout by Schapire. However, I could not find any result for ...
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61 views

Duda, Hart, Stork No Free Lunch Discussion

Please see this question regarding Duda, Hart, and Stork's No Free Lunch Thm Discussion Hi all, I was having trouble understanding the description of the NFL theorem in Duda, Hart, and Stork. My ...
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1answer
39 views

Predicting the impact point of a moving object

Suppose we have a moving object (a horizontal projectile motion as one of the most basic examples). Is there any way to predict where it will hit finally? Please note that I'm looking for a machine ...
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20 views

How much time is reasonable for training Restricted Boltzmann Machine?

I have implemented Binary RBM in Matlab. I am using 60000 images as an input to train RBM. It takes approximately 11.3 minutes. I used tic and toc functions to evaluate above mentioned elapsed time. ...
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1answer
66 views

Variance-covariance matrix for ridge regression with stochastic $\lambda$

In ridge regression with design matrix $X$, outcomes $y$, fixed regularization parameter $\lambda$, and errors $\epsilon\sim\mathcal{N}(0, \sigma^2I)$, the computations for the ridge regression ...
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12 views

GB-RBM unable to learn and generate simple 2D-Motions?

I am trying to apply a GB-RBM to a variation of the LASA Handwriting Dataset to be able to generate new examples. My dataset contains motion trajectories of simple shapes like 'S' shapes, spirals, 'C' ...
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22 views

Bayesian Perceptron - how can I generate many different perceptrons?

I am going to implement the Bayesian version of a perceptron that I read in the Statistical Mechanics of learning, by Engel-Van Den Broeck. The idea to improve the performance is to use many Gibbs ...
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32 views

Conditional or Joint Probability under Various distributions

In various statistical models the baseline equation (like in Naive Bayes $$\mathrm{classify}(f_1,\dots,f_n) = \underset{c}{\operatorname{argmax}} \ p(C=c) \displaystyle\prod_{i=1}^n p(F_i=f_i\vert ...
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1answer
38 views

Where can I use kernels other than Gaussian (like Cauchy, laplacian) in kernel methods in machine learning? Or maybe in kernel density estimation?

In few papers I read that - kernel used doesn't really matter for kernel density estimation but bandwidth of the kernel is the most important factor. But I did not see any mathematical explanation to ...
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5 views

How accurate sum of kernel function needs to be, so that we can use it in Mean shift algorithm (may be for image segmentation)?

Mean shift is a procedure for locating the maxima of a density function given discrete data sampled from that function. It is useful for detecting the modes of this density. This is an iterative ...
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2answers
143 views

Ensembles of Ensembles?

I like the idea of ensemble learners, especially Bagging, but I always wondered as why they are not the most powerful learners since they have a clean motivation. I don't have the answer to that ...
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9 views

How to interpret merits in Weka with ChiSquaredAttributeEval and SVMAttributeEval?

I want to interpret the goodness of attributes using feature selection with 10-fold cross validation. With ChiSquared I get something like this (deletet attributes with merrit was 0 in all folds): ...
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20 views

Predict feature combination with highest probability

I trained a Support Vector Machine with the caret package in R. My dataset looks the following: ...
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16 views

Regression line fit for linearly increasing data with manual reset

I've a linearly increasing time series dataset of a sensor with value ranges between 50 to 150 on which I've implemented a simple linear regression algorithm to fit a regression line, and I'm ...
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9 views

Improving sentence segmentation in NLTK

I have been looking into problem of sentence segmentation lately. I have been referring to NLTK's book for this purpose. I followed their procedure to segment sentences presented here: ...
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28 views

What is the simplest way to classify airplan manuvers?

Suppose we have declared four motion types for air-plane. If we represent each maneuver with a trajectory line, what is the best classification method to retrieve the trajectory pattern with a similar ...
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2answers
184 views

Estimate ARMA coefficients through ACF and PACF inspection

I know that this is probably a question that's been asked plenty of times, but i haven't seen an answer that's both accurate and simple. How do you estimate the appropriate forecast model for a time ...
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0answers
8 views

determing states in HMM with BIC

I'm fitting a HMM to time series, for each data set I use BIC results to select the optimum number of states. In that, the BIC number is lowest and thereby indicating this model with that number of ...
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1answer
95 views

Is KNN a discriminative learning algorithm?

It seems that KNN is a discriminative learning algorithm but I can't seem to find any online sources confirming this. Is KNN a discriminative learning algorithm?
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6 views

Turning MiniBatchKMeans into Fuzzy MiniBatchKMeans

I'm using Scikit-Learn, which has an implementation of MiniBatchKMeans. I'm very inexperienced with ML, so I'm wondering how (if ...
2
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3answers
98 views

Best way to turn a date into a numerical feature?

I have a fairly large dataset with a few fields containing time-related data. This data comes in various shapes and sizes, but most of it can be parsed and rephrased in more appropriate formats for ...
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1answer
30 views

SVM cost parameter

In a SVM with linear kernel, could you explain to me what exactly the C parameter is/represents? An example why it's important to select a good value for C would also be appreciated. Thank you.
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1answer
59 views

Maximum Entropy Model for classification, what to use as context & feature?

I'm building a Maximum Entropy Model to classify some text, based on paper "A Maximum Entropy Approach to Natural Language Processing" by Berger et.al. It's similar to POS tagging. Below is some ...
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37 views

What is this problem called in machine learning research?

Given 2 sets of entities from 2 different classes described by properties $f_1...f_n$, any 2 entities from the 2 different classes together have a score: ${\rm Score}(c_1e_1,c_2e_1) = y$. How ...
2
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1answer
61 views

The usage of data mining in pharmaceutical companies?

I know that data mining applications are being used in pharmaceutical companies, but my question is: what do they use them for? Sometimes I read: "drug discovery", but how? How is it used for drug ...
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9 views

how to create labeled term to document matrix for classification for TMG

I already asked the same question but not got any reply. Please any one help me. I have created term-to-document matrix for document collection. I want to classify them with TMG (Term to matrix ...
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18 views

What are some multivariate models with feature interactions

I have dependent variable matrix $Y_{i,j}$ and feature matrix $X_{i,k}$. My objective is to predict each element of the vector $[y_{i,0},...,y_{i,J}]$ by using new observations of the features, ...
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33 views

Training and testing on Unbalanced Data Set

I used SMOTE algorithm in R for class balancing. My data size has 13000 rows, I had 7% minority class in my sample now I used SMOTE( Synthetic Minority Oversampling Technique) for class balancing such ...