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

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Theano in deep learning research

How widely is Theano used in deep learning research? Is Theano a good start to learn the implementation of machine learning algorithms? Will learning the implementation of something like a feed ...
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Confidence Versus Prediction Intervals using Quantile Regression / Quantile Loss Function

If you fit a quantile regression for the 5th and 95th percentile this is often described as an estimate of a 90% prediction interval. This is the most prevalent it seems in the machine learning domain ...
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Generating features: What level of interaction?

I have multi (3) level data indexed by i,j,t. As such, I can generate fixed effects (dummies) for either ij, it, or jt, (and still achieve identification). I can also do i,j,t separately as well. ...
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Probabilistic Interpretation of Linear Regression

So this has been something I've been studying for some time. The first time I studied it I glossed over the details and parts that I really didn't understand. Now I'd like to tackle these points. My ...
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Natural Language measure of obfuscation

I have some experience with sentiment analysis in natural language processing, but want to learn some new algorithms and techniques for a project I am working on. In particular, I am interested in a ...
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21 views

Machine learning technique for simple predictive model generation

I regularly deal with data in which I have a single metric that is computationally expensive to calculate. I also have numerous (less than a dozen) low-resolution metrics that attempt to approximate ...
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Adjusting Probability for oversampling

I am developing a marketing (Churn) model that has an event rate of 0.5%. So i thought to perform oversampling. I mean making the number of events equal to number of non-events by reducing non-events ...
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14 views

Variable selection with hand on example in R

I am looking for most suitable way to perform analysis (with statistical evaluation) where the aim is to find (select) a suit of continuous (collinear) variables that best describe other continuous ...
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how to combine coefficients of a logistic regression model with existing prior knowledge about covariates?

I am working on developing statistical models for fault-localization. on the one hand, i construct a logistic regression model with these considerations: 1-my dependent(response) variable is program ...
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Language specific words dataset [on hold]

Where can I find a dataset with all(or the most important) words from a language, for example I need a dictionary for roumanian language. Thanks!
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15 views

How to grade a customer on his/her propensity to buy a product? [on hold]

I am working on a project which requires me to grade the person on the scale of 0-100, on the basis of his propensity to buy a product. For this task I have retrieved some data in the form of ...
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16 views

Random Forest online/incremental learning in R

Is there a Random Forest implementation available in R, that supports online learning? My alternative approach was to use the popular randomForest package and combine Random Forests (the existing one ...
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25 views

Features for Object Detection

I want to build a classifier for detecting Airplanes in images. It is important to note that size and shape of the Airplane does not matter in the image. So for training I might simply use the images ...
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Neural Network hypothesis evaluations

If I have a sample data divided into three blocks: training, cross-validation, and test, and we want to evaluate how a model performs, which cost function error are we taking into account? I am ...
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7 views

Enhancing one feature set with another feature set

My problem is I have two feature sets lets say those feature sets as A & B where A does have features A1, A2, A3.... AN and B does have features B1, B2, B3.... BN. 'A' features are computed always ...
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Publishing paper on Recommendation system [on hold]

I'm planning to do research on StackOverflow data dump for recommending questions to users. As an end result I would like to publish a paper on my research. But there is already a paper published ...
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1answer
36 views

How can we learn to classify images that are airplanes ?

The training set is a set of images of the airplanes. Task is : Given an image classify it as an airplane or not. Is it feasible ?
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fuzzy clustering and multi-label classification

I’m working on a clustering problem that I would like to extend to multi-label classification. Basically, I want to generate a number (x) of clusters using something like fuzzy c-means and using the ...
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1answer
28 views

What is a good way to test a simple Recurrent Neural Network

I have coded up a simple real-value regression RNN in theano. What kind of dataset should I test it on? How should I go about testing it? My structure is: Univariate (for now) timeseries, ...
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How to train a Gaussian Mixture Model using Testing Data

My work is to extract HOG features from Arabic Line images and than do classification using Gaussian mixture model to have a look at the performance. My question is after extracting the features how ...
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where to find all the available models for classifications?

I was just wondering is there a reference, like blog, website, book, article etc that would point to all the available models for classifications in machine learning. The more I learn machine ...
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what is the influence of the specific statistical model selection in a practical project

I hope this is the right place to ask this question. But if it is not, please feel free to migrate. There is a famous quote, which is like "all models are wrong, but a few are useful". So, I was just ...
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Ordinary and SVM regression fought, who won? [on hold]

Suppose one would like to construct a regression model for solely prediction purposes. Which one is better and when, ordinary or SVM regression?
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2answers
37 views

General assumptions about functions in machine learning

In the article "A few useful things to know about machine learning" (ungated pdf), I found the following quote: In fact, the general assumptions, like smoothness, similar examples have similar ...
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Clustering Self Organising map nodes

How can i perform unsupervised clustering on the nodes after i have run self organising map. Assuming i have no ground truth of the dataset. I read Density-based Simultaneous Two-level Algorithm for ...
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Trying to perform cluster analysis based on multi-variable data?

I’m struggling with how to find clusters/groups in a large set of multivariable data. Problem: Let’s say I have an ecommerce candy store. At my candy store I have various brands of candies(kitkat, ...
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Marginal likelihood and coordinate ascent

When updating posterior distributions in Bayesian inference using coordinate ascent, is the marginal likelihood of the data guaranteed to increase after each update?
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35 views

Help logistic regression [on hold]

I have to predict a binary variable with logistic regression. The idea is to classify a number of subjects each either sick or not sick. Therefore, I have 11 risk factories for each person and have to ...
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1answer
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Training an Elman Recurrent Neural Network?

I have few doubts related to training Elman RNN using Backpropagation Through Time Algorithm. Assume, I present a sequence to the network and the network adapts the parameters based on the error ...
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online bin packing and machine learning

I am trying to optimize scheduling disk allocation in data centers. In nature it is an online bin packing problem. But, since each customer has it's own behavior or kind of workload I was wondering, ...
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How to detect noisy datasets (bias and variance trade-off)

Studying the bias-variance trade-off: expected loss = bias + variance + noise I understand that we minimize this quantity by finding the "best" balance between ...
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1answer
42 views

Understanding neural networks and classes

I want to know if this argumentation is valid or not of my algorithm. I'm trying to implement a CBIR (Content-Based Image Retrieval) where I've used the basics on CBIRs (colour, texture, shape, ...
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1answer
62 views

What makes the recommendation problem unable to be solved by traditional machine learning algorithms directly?

We have collaborative filtering and content based algorithms there for recommendation. What stops traditional algorithms from directly being used to find missing values in the Utility matrix ...
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1answer
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How to train a Recurrent Neural Network for Temporal XOR?

I have coded a Elman RNN using BackPropagation Through Time. In order to check my implementation, I have chosen Temporal XOR(a sequence of binary digits with the third being the xor of previous two ...
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Machine Learning when missing data is state-dependent (e.g. adaptive questionnaires)

I have the following problem: I am dealing with an adaptive questionnaire, meaning a questionnaire where there are questions that are only asked when a previous question had a specific answer. The ...
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39 views

When using SVMs, why do I need to scale the features?

According to the documentation of the StandardScaler object in scikit-learn: For instance many elements used in the objective function of a learning algorithm (such as the RBF kernel of Support ...
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Maximum Likelihood Algorithm Implementation [on hold]

Hello Guys i have to implement Algorithm of Maximum Likelihood using Hyper-spectral data of 170 bands, have to classify 16 classes using ground truth data. The formula for implementation is as follow, ...
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Why does Alex Graves use a mixture model with his RNN instead of just directly predictive real values?

Alex Graves created a model to generate hand writing sequences which use an LSTM (kind of Recurrent Neural Network) to predict the parameters for an mixture model. The mixture model is then used to ...
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Intuition behind using boolean frequencies in tf and multiplicities in tfidf in gensim

I have a general question about the intuition behind the implementation of the tfidf model in gensim. I understand that by default gensim uses as term frequencies Boolean frequencies, i.e. 1 if term ...
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1answer
31 views

classification error in supervised learning problem

Suppose you have a supervised learning project where it is not easy to check whether the value you predicted is correct or not. So, in this case, does it still make sense to talk about the ...
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2answers
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Machine Learning Methods for Binary Classification

I was hoping to get a nice list of alternatives to logistic regression and decision trees for binary classification ("Yes vs. No" or "Cured vs. Not cured"). I am more interested in identifying the ...
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A book on digital signal processing and control theory for machine learners?

I noticed that digital signal processing (DSP) and control theory (CT) are essential to master machine learning, at least I saw that many great machine learning scholars are experts in these two ...
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[CNN]: Predict label of one single image using DeepLearnToolbox [on hold]

I am using DeepLearnToolbox to do CNN (Convolutional Neural Networks). I have computed my network successfully and I've seen my accuracy, but my question is: How can I query one single image into ...
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What are are some common concepts regarding optimizing a algorithm with forecasted input?

I am a programmer working on a problem where I need to make an optimization based on forecasted data. I feel kinda lost, and would like to find some statistics/machine learning articles on similiar ...
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**Kappa measure in Random Forests** [on hold]

Following is the detailed summary of trained model by Random Forests: ...
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1answer
30 views

How to tune parameters through cross-validation without grid search?

There are actually lots of questions about parameter tuning through cross-validation. I have read some of them, e.g. this one. I, however, still can't understand the details of the process. Here are ...
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1answer
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Variational Inference: good inference but ELBO decreases instead of increasing

I am playing with Variational Inference for clustering within a mixture of Gaussians. My first implementation seems to work fine (this is for the geyser dataset): ...
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How to calculate the probability of a sample to get a specific pattern, given all samples and features?

I have a data aggregation tool, which collects information on many samples (clusters of molecules in this case). So it can create a sparse matrix of NxM binary values (N answers of 0 or 1 for M ...
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Error function of two layer neural network

Let's say we have a two layer neural network with $\theta^1$ and $\theta^2$ as the layer units. Now ${\delta J \over \delta \theta^2}$ is convex and has a global minima for each unit. But what is the ...
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Is validation set always necessary?

Lets say I did the following steps: Used some separate development set to select some features. Decided a priori to use only one learning algorithm (SVM) with only default parameter values. Trained ...