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

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UCI Machine Learning Data Set: Parkinson Speech Dataset with Multiple Types of Sound Recordings Data Set

I would like to use the data set Parkinson Speech Dataset with Multiple Types of Sound Recordings Data Set from UCI to test pattern recognition algorithms. However when I plot the features and ...
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20 views

learing structure of Bayesian Network from data

If I have data and I want to learn the structure of Bayesian Network from these data but the node ordering is not given which algorithm I should use.
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13 views

Pairwise Learning to Rank - detecting detrimental changes

The idea behind Pairwise Learning to Rank is that if you have a set of search results then a clicked on result can be used as training example to indicate that it should rank more highly that the ...
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24 views

What does improper learning mean in the context of statistical learning theory and machine learning?

I was reading the following paper and it talked about improper learning. I wasn't 100% what it rigorously meant but they do mention: I am not sure what "representation independent" means, but as ...
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1answer
59 views

Using Neural Networks to predict stock values

How are neural networks usually used to predict market evolution? My data consists of a set of pairs (time, value), taken at an interval of 15 minutes. My ideas so far are: I.Take 40 values (or ...
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2answers
124 views

How to make sure that a machine learning algorithm's implementation is correct?

Say there is a machine learning algorithm (e.g. classification) that is well known and implemented by the original creators of the algorithm. Yet all you have is the ability to use the algorithm but ...
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2answers
55 views

Data splitting and cross validation

my question is about splitting data! I used to split data into training and testing set using caret library in R ...
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26 views

Caret feature selection [RFE] yields different features depending on reference level of binary outcome

I'm using RFE from the caret package in R to select variables to be used in a linear discriminant analysis. The outcome is a binary factor, but depending on which level of the factor is used as the ...
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1answer
34 views

distinction between Bayesian Network and another graph [closed]

I want to ask if we have two graph one of them Bayesian Network and the other one just regular graph, how we can distinction between them.
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9 views

Feature Selection for Brain Data

I am trying to make the binary prediction of a certain behavior (present=1, absent=0) from brain activity. I have data from 100 people each with about 40,000 features (regions of brain activity in the ...
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16 views

Difference in training procedure for DBN and DBM

This is related to the following thread Deep belief networks or Deep Boltzmann Machines? but it doesn't seem to answer in a practical sense what the difference is. So I gather a DBN is directed and ...
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1answer
98 views

Does the opposite of nested cross-validation make sense?

I'm asking the question from a machine learning point of view. I have a dataset with relatively high sparsity, so if I use nested cross-validation for my feature tuning and evaluation, that is tune ...
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2answers
289 views

My Test accuracy is pretty bad compared to cross-validation accuracy

I did a Multi-class document classification. I divided the original data set (18,8334 documents as a list of strings where each element of list is a document string.) into 70% training and 30% test. ...
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3answers
66 views

Criteria for classification performance

In binary classification, are there criteria or guidelines available to judge if classification performance of the testset (unseen data) is poor, medium or high? I realise that this may depend on ...
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1answer
70 views

Machine learning for pattern recognition in realtime sensor data

I'm working on a project where we need to detect patterns in a sensor's output to find out if a given event occurred. Given my limited experience with machine learning, I was wondering if someone ...
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27 views

customer analysis - book / blog recommendation?

I'm new to the topic 'customer analysis' (in general) and need advice for a good starting point: What is a good book / blog / tutorial on this topic? My current situation is: I have a lot of customer ...
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1answer
25 views

Class-specific feature importance

I have rather a simple question which I have not had any luck finding the answer to. I'm training a Random Forest classifier using sklearn in Python 2.7, on a large dataset ~(80k,250) where ...
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14 views

MANOVA application

Need to check whether it is mandatory to have at least one continuous DVs in MANOVA, also does sample size of 2 groups matters much, i am planning to check whether recruits from campus or off-campus ...
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2answers
50 views

Nested cross-validation - how is it different from model selection via kfold CV on the training set?

I often see people talking about 5x2 cross-validation as a special case of nested cross validation. I assume the first number (here: 5) refers to the number of folds in the inner loop and the second ...
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2answers
65 views

Why don't people use deeper RBFs or RBF in combination with MLP?

So when looking at Radial Basis Function Neural Networks, I've noticed that people only ever recommend the usage of 1 hidden layer, whereas with multilayer perceptron neural networks more layers is ...
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18 views

Algorithms for Suggesting Users

There are often a large number of bug tickets that get generated for the projects at my company. I was thinking of an intelligent way for automatically suggesting users to assign to the tickets based ...
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26 views

NaiveBayes, J48 and RandomTree in layman's terms

I am difficulty understanding how both classifiers work under the hood. So far I have deduced NaiveBayes predicts an outcome by 'uncoupling' multiple pieces of evidence, and to treating each of piece ...
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20 views

Huffman tree generation if the frequency is same for all words [migrated]

Can a valid Huffman tree be generated if the frequency of words is same for all of them? Example : ...
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13 views

Implementing PCA using Incremental approach [migrated]

I am trying to implement the algorithm proposed in the paper in Section (III) here in R. It uses incremental eigendecomposition and incremental SVD for calculating IPCA. Instead of working on images ...
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43 views

Knn classifier for Online learning

Is Knn classifier suitable for online learning i.e. Is it effective to apply online learning approach for knn classifier?
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1answer
35 views

Backward propagation algorithm demonstration in neural networks: any VERY-SMALL-STEP by VERY-SMALL-STEP demonstration?

I'm looking for a VERY DETAILED demonstration for the backward propagation algorithm in neural networks machine learning. Specifically the step below. I've got the excellent Michael Nielsen ...
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25 views

When is logistic regression minimizing under squared error loss the same as maximizing binomial likelihood?

Implementing logistic regression and getting different results depending on whether I minimize squared error or maximize log likelihood. When are the two equivalent?
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2answers
83 views

Are N-1 distinct points with two classes Linearly Separable in an N Dimensional Space

I have this conjecture whose verification I haven't been able to find online anywhere. If you have N - 1 distinct points that each have one of two classes, can you find a linear decision boundary in ...
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1answer
74 views

Why am I getting 100% accuracy for SVM and Decision Tree (scikit)

I have a dataset with 1175 examples and 21 features which are in the range of [-1, +1], and two class labels 1 and 0. As I read in the most of the resources, it is good to have data in the range of ...
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1answer
36 views

Choosing right range for data while using scikit-learn

I have a dataset with 1175 examples and 21 features which are in the range of [-1, +1], and two class labels 1 and 0. As I read in the most of the resources, it is good to have data in the range of ...
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2answers
46 views

Using k-means for reducing the size of the training set of a Kernel SVM

I have a classification problem with the following characteristics: a few million data points around one hundred features non-linearly separable Training a SVM with an RBF Kernel is not feasible ...
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3answers
52 views

Question regarding form of a cost function while training a model

I am beginner in Machine Learning and I am very interested in modelling, simulation and all this jazz :) One of the basic idea I learned so far is the use Cost Function and its minimization in order ...
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42 views

How to measure error in linear regression?

Suppose I have $X, Y =$ {$(x^{(1)}, y^{(1)}); (x^{(2)}, y^{(2)}); ...; (x^{(m)}, y^{(m)})$} examples with: $x^{(i)} \in \Re^n$: for $i$ $\in$ [1;m], $x^{(i)}$ = {$x_1^{(i)}, x_2^{(i)}, ..., ...
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2answers
77 views

Large? Number of parameters in MCMC model [closed]

I am implementing a Hierarchical Bayesian Modeling in order to model the relation between the independent and dependent parameters $(x, y)$. I assume the relation is: $$ y_i = \alpha + \beta x_i + ...
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1answer
247 views

How does the mean function work for a Gaussian Process?

I was reading the notes on Gaussian Processes by Choung B. Do (stanford course CS229) however was unsure of how the mean function worked and what a random variable was on the Gaussian Process So ...
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64 views

How to combine weak classfiers to get a strong one?

Let as assume that we have a binary classification problem. We also have several classifiers. Instead of assigning a vector to a class (0 or 1) each classifier returns a probability that a given ...
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27 views

How to input sparse feature

In theano everything is symbolic, so how to input sparse feature in , for example, neural network? The setting is: the task is text application. the input is a mini-batch. Since theano sparse module ...
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1answer
29 views

Guessing the word from context

Can I train a system to decide, which one of suggested words is more likely to appear in the sentence being analyzed? For example, if I have sentence "I was playing with my ______ when I heard the ...
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1answer
25 views

What is the predictive distribution of Bayesian supervised Learning? (rigorous argument)

I was trying to understand the posterior predictive distribution for any supervised predictor (by that I mean any classifier or regression predictor $f$). The exact equation I am unsure of is: $$ ...
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1answer
46 views

SVM parameter tuning for unbalanced classes (with class weights)

I am trying to run an SVM on an imbalanced dataset (0-90%, 1-10%) using the e1071 package, with the radial kernel. I am using cross-validation to select the best gamma and cost. Additionally, I want ...
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25 views

Most efficient SVM implementation

I'm currently using LIBLINEAR to perform linear SVM on a very large data set that sometimes collapses. Is there a more efficient implmentation of SVM? UPDATE: The C version of liblinear collapses, ...
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92 views

Classifer for unbalanced dataset?

Is there any classifer that can natively support unbalanced datasets? Or what best practices you can suggest to handle such datasets? For example I want to solve task called "pedestrian detection" ...
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32 views

My Cross-validation error is always increasing with increasing regularisation parameter

I am not sure what is happening, but my cross-validaton error is always increasing with increasing alpha in ridge regression. It should technically go down and then increase. Here is what I am doing ...
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1answer
27 views

Very low Rsquared of Lasso on Test sample. But very low MSE too?

I am not sure what is going wrong here. I did the following : ...
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8 views

Merging two different segmentation solutions into one

I have the following problem: two different segmentation analysis to do, one using needs/motivations for consuming a product and one related to general attitudes toward product category and lifestyle. ...
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5 views

best method for calculating sales for keywords

I have a set of keywords and searches made on those keywords. Each keyword search has produces a number of products. Knowing how many units each product sells, and hypothetically knowing every ...
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Looking for a principled/systematic procedure for discarding features

I have a collection of $M_i \times N$ matrices $X_i$ whose rows are (raw) feature vectors (from a common $N$-dimensional feature space). MATLAB reports that most of the covariance matrices $C_i := ...
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15 views

Difference between Bag of words and Vector space model

I am searching for the intuitive difference between Bag-of-words and vector space model? Is there any relationship exists between bag-of-words and vector space model. I tried searching but couldn't ...
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61 views

Machine Learning: curve completion using sets of completed curves

I am very new to the world of machine learning and i am wondering if a) machine learning is able to solve the problem b) whats the best way to do it (pref with example) I have a set of curves for a ...
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88 views

Reconciling boosted regression trees (BRT), generalized boosted models (GBM), and gradient boosting machine (GBM)

Questions: What is the difference(s) between boosted regression trees (BRT) and generalized boosted models (GBM)? Can they be used interchangeably? Is one a specific form of the other? Why did ...