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

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Using PyBrain after training a network

I'm using PyBrain to create a neural network. I'm still pretty new to neural networks and their concepts. I've so far only run train() over the network, as ...
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22 views

How to get random classification to assess the performance of classifier with McNemar test?

I'm trying to replicate a study where the author used the McNemar test to assess the performance of classification compared to random classification. I have the original classifier and I'm using R to ...
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81 views

How to categorize classifiers and matrix factorization methods?

I have a classification problem which is solved by a variety of methods. Among the methods are unsupervised methods, traditional classifiers and a supervised matrix factorization methods. The problem ...
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1answer
27 views

How do I incorporate the biases in my feed-forward neural network

I'm trying to implement a FFNN. I'm doing this as an excercise to understand how biases play a role in the classification. I trained a NN using a package in R with the inputs being 1..100 and the ...
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2answers
57 views

Why Adaboost with Decision Trees?

I've been reading a bit on boosting algorithms for classification tasks and Adaboost in particular. I understand that the purpose of Adaboost is to take several "weak learners" and, through a set of ...
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1answer
68 views

Gaussian is conjugate of Gaussian?

Someone told me that, Gaussian distribution is conjugate to distribution because a Gaussian times a Gaussian would still be Gaussian distribution ? Why is that ? Say the following situation: $X\sim ...
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16 views

Predicting the near-future values using an unevenly sampled time-series data

Summary Need help with predicting the near-future values using an unevenly sampled time-series data. Data is collected as events, and is converted to time series. I have tried out a few approached ...
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19 views

Why all coeficents of features of model are zero while I have high deviance using glmnet?

I'm using gmlnet to learn lasso regression model. model<-cv.glmnet(x, y, alpha=1, nfolds=10,parallel= TRUE) when I learn model and look at the model it's like this : ...
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35 views

NLP tokenization for building feature vector

I am trying to match new product description with the existing ones. Product description looks like this: Panasonic DMC-FX07EB digital camera silver. These are steps to be performed: Tokenize ...
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23 views

Machine learning and Partial differential equations

Are there any algorithms which were developed using partial differential equations for tackling some of the machine learning problems? Most works I see online are in the field of computer vision and a ...
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15 views

data amplification

I have obtained few data points from my client, and want to increase the number of data points keeping the complexity of the original almost same. and in the second part increasing the data ...
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25 views

A measure of correspondence between ranked ordinal data

I would like to find an appropriate way to measure the similarity between two sets of data with the following characteristics: Both sets contain 10 categorical observations. The categories ...
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1answer
57 views

How to handle missing data in a small $n$ large $k$ machine learning scenario?

I have a sample size $N=130$ and $1000$ variables. I am using machine learning techniques (SVM) for analysing the data. Some variables in the dataset have values that are so huge that they must be ...
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16 views

How process mining compares to probabilistic model (PGM)?

process mining can discovery graph model of process, so can probabilistic-graphical-model (...
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22 views

R, Confusion Matrix in percent [migrated]

In R how to get Confusion Matrix in percent (or fraction of 1). The "caret" package provides useful function but shows absolute number of samples. ...
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16 views

Standard error of prediction MARS splines earth package

I'm using the earth package (using caret train function) MARS spline implementation in order to perform non - linear regression modeling. I would like to obtain a measure of prediction uncertainty ...
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1answer
60 views

Ratio between positive and negative examples in a training problem

When training a 0/1 classifier, what should be the ratio of positive to negative, how to decide the ratio between them based on the classifier I use and the data set under analysis?
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8 views

Grouping team features and comparing them to a single match outcome

I have two teams, and both teams have multiple features related to that team. For example: Players in the team. Players total points won. Team win percentage. Average player weight. Average player ...
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15 views

Is the approach for PLSDA for categorical variables the same as that used for “PLS for regression”?

I understand the approach used for partial least squares for regression (PLS) where the principal components are chosen such that the correlation between the scores in the principal component space ...
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1answer
26 views

Label propagation in semi-supervised learning

Suppose we have a set of labeled and unlabeled instances. 70%unlabeled 30% labeled. We apply a semi-supervised algorithm. Let's say we apply S3VM or Laplacian SVM. We use all the data available. When ...
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22 views

Machine Learning books for CS (non-statistician) grad student [duplicate]

What books on machine learning are recommended for a CS graduate student without a huge background in statistics? I do have some background in ML (and of course linear algebra, probability, etc.) but ...
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61 views

Assume (x,y) are drawn from independent & identical distribution when y=f(x)

Sometimes we say the following: $X$ is some training data given by $X:=\{(x_1,y_1),...,(x_l,y_l)\}\subset R^d \text{x}R$. Assume that the training data had been drawn from independent and identical ...
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42 views

Learning Decision Trees on Test Data Using R

How can I use R to learn classes on test data? I currently have a training set of about 1000 entries and a test set of about 10000 entries. I split it up so that the training set has the class label ...
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15 views

Optimal Margin Classifer : Optimization Problem Setup

In the notes from Andrew Ng Machine Learning course, he writes the initial optimization problem as follows. I am confused by the notation and suspect I am missing something simple. Given the ...
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26 views

Greedy subtree selection in Nested Hierarchical Dirichlet Processes

I'm implementing the Nested Hierarchical Dirichlet Process as described in this paper by Paisly et. al, 2014: http://arxiv.org/abs/1210.6738 My question is about the variational objective in Equation ...
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1answer
21 views

What is the intuition behind the Kappa statistical value in classification

I understand the formula behind the Kappa statistic value and how to calculate the O and E value from a confusion matrix. My question is what is the intuition behind this measure? Why does it work so ...
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1answer
23 views

How to choose an appropriate maxdepth in rpart.conrol?

I'm using the boosting method in adabag library and trying to choose an appropriate maxdepth in rpart.control for building a 2-class classification model using my training dataset. I have noticed that ...
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16 views

Can you use accelerometer data for classification with Conditional Random Fields?

I want to recognize activities, based on accelerometer data from the smartphone. I studied Conditional Random Fields and the CRFSuite. Now I am Confused. In my opinion CRF training uses static single ...
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38 views

Vector Space Model for Online News Clustering

I am trying to automatically cluster news articles based on their content. I need this algorithm to be online and simply group news articles related to the same story as they arrive. The common ...
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15 views

Classification with two different dataset

I am working on a cancer classification model.Task is ,I am initially given a data set of 500 people and 1000 features.These people are given some kind of treatment(say Treatment 1). Some people are ...
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2answers
65 views

Split clustered data into calibration and validation sample (Cross validation)

I have a dataset with >800 cases ($n$) from >30 ($k$) different organisations (clustered data). The number of cases within each organisation differ (unbalanced data; e.g.: organisation 1 = 30 cases, ...
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1answer
59 views

R caret package - number of principal components when preprocessing using PCA

I am using the caret package in R for training of binary SVM classifiers. For reduction of features I am preprocessing with PCA using the built in feature [preProc=c("pca")] when calling train(). How ...
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1answer
72 views

Better in ROC AUC vs. better in PR AUC

I'm comparing two classification models by computing the area under ROC and Precision-Recall curves. However sometimes one model is better with AU-ROC but worse in AU-PR, and other times it's better ...
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1answer
74 views

How does Support Vector Machine compare to Logistic Regression?

Support Vector Machine (SVM) and logistic regression (LR) have been discussed widely in machine learning community, I know that both of them achieve pretty good performance. But, I am not sure how in ...
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19 views

ANOVA and Principal Component Regression

I Just need your valuable suggestions. ...
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35 views

Data Augmentation using Eigenvalues and Eigenvectors

Recently, I have come across a paper which has used a unique way of augmenting the data. If the data has multiple channels say we have a $x_i , i=1...N$ as a column feature vector. If we compute the ...
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44 views

How to best to use Continuous value features with discreet values for logistic regression based binary classification problem

This is related to Minimisation algorithm for a mix of discreet and continuous parameters? I am trying out logistic regression to solve a binary classification problem. Though I am feature-scaling ...
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1answer
34 views

Understanding SVM and when to precompute the normal vector

I've been reading a lot about SVMs and have some questions about performing classification from the SVM model produced from a package like libSVM. From my understanding, for a linear SVM without the ...
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34 views

One or two output neurons for a binary classification task with an artificial neural network

Suppose you have a classification problem in which you want to classify inputs into two exclusive classes (y1 and y2) with an artificial neural network (which models P(y|x)). Among the two following ...
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59 views

“…if the data is linearly separable”

I keep hearing this phrase as a precursor to many algorithms, but I am not sure how exactly one goes about finding out if the data is indeed, linearly separable. Of course, if the data has ...
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2answers
55 views

Using a gaussian kernel in SVM. How exactly is this then written as a dot product?

I am attempting to use SVMs for my class project. For this project, I have selected the gaussian kernel as, well, the kernel. That is, $$ k(\mathbf{x}_1, \mathbf{x}_n) = e^{-\gamma ||\mathbf{x}_1 - ...
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30 views

R PNN slow- other packages?

I'm trying to run a pnn (Probabilistic neural network) in R, using pnn package. It's function smooth uses rgenoud package to optimize. I only used 9k lines and it's real slow. Is there any other ...
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38 views

What is AUC of PR-curve?

I understand that AUC under ROC curve is a classic evaluation measurement for classifiers (which is basically the accuracy). However, when data is imbalanced, PR will be alternative. So, what does the ...
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1answer
31 views

Pattern recognition in state sequences

I have a sequence of states of a system. Each state is defined by an abstract identifier e.g "Eating", "Sleeping" etc... and a duration. So a state is basically ...
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1answer
27 views

Have difficulty understanding Matlab's Ridge regression

I am confused by Matlab's documentation of Ridge regression at http://www.mathworks.com/help/stats/ridge-regression.html and couldn't figure it out by myself. On that page, the Introduction to Ridge ...
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30 views

SVM One-vs-One vs One-vs-ALL SVM

For an unbalanced dataset annotated by human annotators in which each item is assigned to different classes, what is the argument for and against using any of One-vs-One vs One-vs-ALL SVM ...
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80 views

How to determine the optimal threshold for a classifier and generate ROC curve?

Let say we have a SVM classifier, how do we generate ROC curve? (Like theoretically) (because we are generate TPR and FPR with each of the threshold). And how do we determine the optimal threshold for ...
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2answers
46 views

Strategies for parallelising neural networks

When it comes to parallelising a problem, it involves the division of routines and subroutines between a number of nodes, namely; the master node and the slave nodes. Once each of these nodes ...
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1answer
54 views

Predicting continuous output

I'm trying to predict output per worker for given inputs of capital (physical capital), labor (human capital) & productivity. I have a data set of several countries ...
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65 views

What are the differences between AUC and F1-score?

F1-score is the harmonic mean of precision and recall. The y-axis of recall is true positive rate (which is also recall). So, sometime classifiers can have low recall but very high AUC, what that ...