Questions tagged [machine-learning]

Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.

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How to update weights in a neural network using gradient descent with mini-batches?

[I've cross-posted it to cross.validated because I'm not sure where it fits best] How does gradient descent work for training a neural network if I choose mini-batch (i.e., sample a subset of the ...
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1answer
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Handling a feature with multiple categorical values for the same instance value

I have data in the following form: table 1 id, feature1, predict 1, xyz,yes 2, abc, yes table2 id, feature2 1, class1 1, class2 1, class3 2, class2 I could perform a one many join and train on the ...
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“Trending” feature to predict number of views

I am working on a problem where I have access to a database with news articles, their publication date and the number of views they got 24hrs they got published. The objective is to be able to ...
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How to create Self learning data product

I am trying to build price recommendation solution for clients in a scalable manner. I have two choices as below. Professional service: Statistician involvement to build regression model or any ...
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What is the difference between affinity matrix eigenvectors and graph Laplacian eigenvectors in the context of spectral clustering?

In spectral clustering, it's standard practice to solve the eigenvector problem $$L v = \lambda v$$ where $L$ is the graph Laplacian, $v$ is the eigenvector related to eigenvalue $\lambda$. My ...
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sklearn - overfitting problem

I'm looking for recommendations as to the best way forward for my current machine learning problem The outline of the problem and what I've done is as follows: I have 900+ trials of EEG data, where ...
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1answer
750 views

How to visualize (make plot) of regression output against categorical input variable? [closed]

I am doing linear regression with multiple variables. In my data I have n = 143 features and m = 13000 training examples. Some of my features are continuous (ordinal) variables (area, year, number of ...
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Why does applying PCA on targets causes underfitting?

The goal: I am new to machine learning and experimenting with neural networks. I would like to build a network that takes as an input a series of 5 images and predicts the next image. My data set is ...
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Which Machine Learning book to choose (APM, MLAP or ISL)? [closed]

I'm searching a book as a refresher in machine learning (I have taken a lecture in machine learning sometime ago). I will be applying machine learning in a project. I have searched a lot of books and ...
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Minimum Error Rate Training using Powell Search for Machine Translation

From the tutorial slides: http://mt-class.org/jhu/slides/lecture-tuning.pdf, (slide 37) the powell search algorithm goes as such: ...
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Pylearn2 vs TensorFlow

I am about to dive into a long NN research project and wanted a push in the direction of Pylearn2 or TensorFlow? As of Dec 2015 has the community started to lean one direction or another? This link ...
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1answer
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Terminology: SOMs, batch learning, online learning, and stochastic gradient descent

I'm not sure which word to use to differentiate a self-organizing map (SOM) training procedure in which updates for the entire data set are aggregated before they are applied to the network from a ...
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Missing features for classifier [closed]

If I am given 60 features along with test label and I was to find values of other features what is the best way to do it ?
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Do I have to standardize my new polynomial features?

I have a vector X with n features previously standardized. If I want to generate new polynomial features (let say adding square features), do I need to do another standardization on these new ...
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1answer
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Predicting app usage on mobile phone

I'm currently building an app that strives to predict how the users uses different apps and give the user a suggestion based on which apps it think the user will currently use (a ranked list based on ...
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1answer
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Categorical and ordinal feature data representation in regression analysis? [closed]

I am trying to fully understand difference between categorical and ordinal data when doing regression analysis. For now, what is clear: Categorical feature and data example: Color: red, white, black ...
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Finding Patterns in continuous data

I'd like to find frequent patterns in data that has been created by an accelerometer of a Smart Watch. The algorithm should return the parts of the data that occur after a pattern. In the best case, ...
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1answer
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In image classification/recognition how are images coded?

I am trying to understand how images are coded for classification/recognition. Suppose that I have images that contain animals (e.g. dogs, cats, birds) -- does each image have a label for that animal ...
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What is the term for when a model acts on the thing being modeled and thus changes the concept?

I'm trying to see if there is a conventional term for this concept to help me in my literature research and writing. When a machine learning model causes an action to be taken in the real world that ...
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How do I perform Naive Bayes Classification with a Bayesian Belief Network?

I've been writing a java library that I want to use to build Bayesian Belief Networks. I have classes that I use to build a Directed Graph ...
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Which Spark MLlib regression algorithm is suitable for numeric predictions based on non-numeric features?

I am working on Spark MLlib and have a project where I have to make predictions for numeric data based on non-numeric features. I am a bit confused about which <...
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Theoretical treatment of unlabeled samples

In a typical supervised learning setting with a few positive and a few negative examples, it is clear that unlabeled data carries some information that can benefit learning and that is not captured in ...
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How to use Cohen's Kappa as the evaluation metric in GridSearchCV in Scikit Learn?

I have class imbalance in the ratio 1:15 i.e. very low event rate. So to select tuning parameters of GBM in scikit learn I want to use Kappa instead of F1 score. My understanding is Kappa is a better ...
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Impact of unlabelled documents for label prediction via SVM

I have a corpus of text documents, some of which are labelled by analysts with label L. I am using this data to train an SVM for predicting if a new document should have label L. So far it's straight-...
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When do I have to use aucPR instead of auROC? (and vice versa)

I'm wondering if sometimes, to validate a model, it's not better to use aucPR instead of aucROC? Do these cases only depend on the "domain & business understanding" ? Especially, I'm thinking ...
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Consolidating values for predictive modelling through Random Forest

I am working on developing a predictive model using Random Forest. There are a lot of users that log in to the site but only a fraction of them actually monetize on that day. I am trying to predict ...
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1answer
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How to place XGBoost in a full stack for ML?

Is XGBoost complete by itself for prod-strength machine learning? If not, with which other tools or libs is it typically combined, and how? (I recently read a description of a stack that included ca ...
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Are there any machine learning algorithms that focus on comparing items, rather than classification or regression?

This is more of a hypothetical than something I'm actively trying to solve. It just struck me that a machine learning algorithm that specifically looked at two pieces of data and had to label one as ...
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1answer
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Can I apply Hidden Markov Models this way?

I have just gotten my feet wet with Hidden Markov Models. Now I want to apply them to tell whether a transaction from an ATM is suspicious or not. I have great confusion in defining my Hidden States. ...
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With unbalanced class, do I have to use under sampling on my validation/testing datasets?

I’m a beginner in machine learning and I’m facing a situation. I’m working on a Real Time Bidding problem, with the IPinYou dataset and I’m trying to do a click prediction. The thing is that, as you ...
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1answer
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Can the size of a pooling layer be learned?

As far as I understood it, the pooling layer doesn't learn anything. It has several parameters, most important its pool_size and ...
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2answers
346 views

Question on reservoir sampling

I have a general question on reservoir sampling. When I use this method to sample a very large dataset for training machine learning classification algorithms, I am curious as to how to make my ...
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Estimating probability using boltzmann machine

I am reading about Boltzmann machines and according the formulas the joint probability of the states of all units is $$ P(X = x) = \frac{1}{Z} e^{-\frac{1}{2T} \sum_i\sum_j {x_i x_j w_{ij}}} $$ $$ Z = ...
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Choosing between Storm+Trident-ML, Storm+SAMOA or Spark Streaming+MLlib

I want to implement Streaming Naive Bayes in a distributed system. What are the best approach to choose framework. Should I choose: Storm alone and implement streaming naive bayes on my own in storm ...
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Distance calculation/vector range significance

I'm trying to implement item based collaborative filtering. Do any distance calculations allow for weighting of certain ranges of values within each vector? For example, I would like to be able to ...
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1answer
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how to make new class from the test data

I have a list of accounts as data set and I need to group the accounts that refer to the same user using many features. I'm thinking to use machine learning( but I'm new in this domain), because I ...
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1answer
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Is there any difference between feature extraction and feature learning?

It appears to me that "feature extraction" and "feature learning" are equivalent concepts, however there are 2 separate wikipedia articles dedicated to them that are notably different. In particular, ...
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collaborative filtering using graph and machine learning

What are the advantages and disadvantages of using Collaborative filtering based recommendation using machine learning approach and graph based approach ? Say I have user purchase data (user_name, ...
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1answer
970 views

Machine Learning algorithm to predict an outcome where output is not known

I have a very unique problem that I would like to solve using machine learning. I have a set of 90 or so unique options. Each of these options has a unique set of features (5 to be specific) that vary ...
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when speed is not a major concern, what is the best ML algorithm for high dimensional data?

we are trying to build a predicting model using machine learning algorithms. I have a use case where the input data have a very high dimension. Each sample point has 20000 features. we have a decent ...
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1answer
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Predictive analysis of rare events

I'm trying to predict rare events, meaning less than 1% of positive cases. I basically try to predict if a subject will have 0, 1, 2 ... , 6, > 6 failures (there are cases in all those categories). I'...
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Voting combined results from different classifiers gave bad accuracy

I used following classifiers along with their accuracies: Random forest - 85 % SVM - 78 % Adaboost - 82% Logistic regression - 80% When I used voting from above classifiers for final classification, ...
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1answer
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Query related to Matlab Neural Network toolbox

If anyone has used the Neural Network toolbox in matlab, what does the two values in the performance section means? Like considering this image: The performance section has the value 0.484 and 1.32e-...
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Are there any machine learning techniques to identify points on plots/ images?

I have data for each vehicle's lateral position over time and lane number as shown in these 3 plots in the image and sample data below. ...
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1answer
436 views

Identifying outliers in an unknown distribution

I have a sorted sequence of integers, e.g. 1,2,480,1000,1100 representing volumes in some categories. The task is to separate the valid data (high volumes) from ...
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1answer
670 views

How to visualize data of a multidimensional dataset (TIMIT)

I've built a neural network for a speech recognition task using the timit dataset. I've extracted features using the perceptual linear prediction (PLP_ method. My features space has 39 dimensions (13 ...
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1answer
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Discovering non-interesting attributes

I would like to ask a question about recommender systems. We are showing some movies to users and they have to decide if they like them or not. These movies have only a few attributes Title Director ...
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3answers
886 views

How to train a Text Based data for a Machine Learning problem?

I am working on a project for displaying products to customer by context, based on a search query. For example, I don't want customers to have to enter a specific product name, instead searching based ...
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Find most representative image

I have 1,000 photoshoot-quality images of pianos on white background with very little noise (people in the background, etc). How would I go about finding the piano image that looks most like the ...

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