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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2
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0answers
132 views

“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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2answers
202 views

Can PyLearn do everything that Theano can?

Since PyLearn2 is build upon Theano, is it possible to do anything I can do in Theano in Pylearn2? For example, if I have some snippets of Theano code, can I run them as-is in Pylearn2, or would this ...
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1answer
10k views

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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0answers
202 views

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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3answers
1k views

How do AI's learn to act when the problem space is too big

I learn best through experimentation and example. I'm learning about neural networks and have (what I think) is a pretty good understanding of classification and regression and also supervised and ...
2
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1answer
110 views

Machine learning worker performance features for optimum allocation of tasks to workers

Suppose we have an English to French translation task in a company, and there are 100s of workers who are proficient in doing this task, but each worker has its own unique attributes which enables ...
140
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5answers
157k views

The cross-entropy error function in neural networks

In the MNIST For ML Beginners they define cross-entropy as $$H_{y'} (y) := - \sum_{i} y_{i}' \log (y_i)$$ $y_i$ is the predicted probability value for class $i$ and $y_i'$ is the true probability ...
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1answer
745 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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1answer
253 views

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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0answers
73 views

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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2answers
4k views

Why is finite precision a problem in machine learning?

Can you explain what is finite precision? Why is finite precision a problem in machine learning?
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1answer
1k views

Troubleshooting Neural Network Implementation

I've been going through the Standford/Coursera Machine Learning course; and it's been going pretty well. I'm really more interested in the understanding of the topic than getting the grade from the ...
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2answers
5k views

Why do activation functions have to be monotonic?

I am currently preparing for an exam on neural networks. In several protocols from former exams I read that the activation functions of neurons (in multilayer perceptrons) have to be monotonic. I ...
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1answer
52 views

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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5answers
33k views

Decision tree vs. KNN

In which cases is it better to use a Decision tree and other cases a KNN? Why use one of them in certain cases? And the other in different cases? (By looking at its functionality, not at the ...
4
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1answer
810 views

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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2answers
2k views

Is Maxout the same as max pooling?

I've recently read about maxout in slides of a lecture and in the paper. Is maxout the same as max pooling?
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2answers
843 views

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 ...
2
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0answers
388 views

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, ...
4
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1answer
14k views

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 ...
4
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2answers
19k views

What does RMSE points about performance of a model in machine learning?

I am working on Decision Tree algorithm and at the end I calculate RMSE value based on actual labels and predicted values (for ...
12
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2answers
59k views

When to choose linear regression or Decision Tree or Random Forest regression? [closed]

I am working on a project and I am having difficulty in deciding which algorithm to choose for regression. I want to know under what conditions should one choose a <...
2
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1answer
148 views

Forecasting an individual based on a representative group

I’m trying to create a model to forecast demand/expenditure for an individual based on historical data of many individuals over time, but I’m having trouble finding examples of this. To give a ...
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3answers
6k views

Gradient boosting algorithm example

I'm trying to fully understand the gradient boosting (GB) method. I've read some wiki pages and papers about it, but it would really help me to see a full simple example carried out step-by-step. Can ...
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1answer
17k views

Server log analysis using machine learning

I was assigned this task to analyze the server logs of our application which contains exception logs, database logs event logs etc. I am new to machine learning, we use Spark with elastic search and ...
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2answers
466 views

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 <...
4
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2answers
3k views

How to extract important phrases (which may contain company name) from resume?

I have thousands of CV / resumes with me. We want to build a parser which can extract company names from resume. So far we have tried Maintained a list of common words present in companies (Eg. Org,...
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8answers
3k views

Purpose of visualizing high dimensional data?

There are many techniques for visualizing high dimension datasets, such as T-SNE, isomap, PCA, supervised PCA, etc. And we go through the motions of projecting the data down to a 2D or 3D space, so we ...
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1answer
390 views

Result Dithering? Why randomly shuffle results?

Most of us want to build a recommendation engine as accurate as possible, however, an experienced chief data scientist believes a practical machine learning algorithm should randomly shuffle the ...
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2answers
92 views

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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2answers
325 views

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 ...
8
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1answer
2k views

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
7k views

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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0answers
77 views

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 ...
6
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1answer
1k views

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 ...
7
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1answer
642 views

data science / machine learning resources? [closed]

In a few weeks I'm starting a new job that will be involved in machine learning and data science. I have a masters degree in probability / mathematics but I have no knowledge of machine learning and ...
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2answers
193 views

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-...
2
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1answer
260 views

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. ...
13
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5answers
11k views

Best Julia library for neural networks

I have been using this library for basic neural network construction and analysis. However, it does not have support for building multi-layered neural networks, etc. So, I would like to know of any ...
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3answers
5k views

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 ...
13
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2answers
5k views

What to do when testing data has less features than training data?

Let's say we are predicting the sales of a shop and my training data has two sets of features: One about the store sales with the dates (the field "Store" is not unique) One about the store types (...
10
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1answer
243 views

User-product positive (click data) available. How to generate negative (no-click data)?

Its very common in recommender that we have user product data which have label as an e.g. "click". In order to learn the model, I need click and no-click data. Simplest approach to generate is to ...
17
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3answers
11k views

Bagging vs Dropout in Deep Neural Networks

Bagging is the generation of multiple predictors that works as ensamble as a single predictor. Dropout is a technique that teach to a neural networks to average all possible subnetworks. Looking at ...
3
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1answer
116 views

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 ...
5
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1answer
48 views

Completing MDS manually in R

Given a matrix A, I want to complete Multidimensional Scaling by hand, instead of using any given R functions. As such, I have calculated the centered matrix ...
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2answers
1k views

Python distributed machine learning

I occasionally train neural nets for my research, and they usually take quite a long time to run (especially when I'm working on my laptop). I'm looking for a way to build the model on any computer ...
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4answers
2k views

oversampling plus down sampling using smote not working on random forests

I am trying to solve a classification problem on a highly imbalanced data set. I am using SMOTE to over sample the minority samples and down sample the majority ones. After creating a balanced data ...
2
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0answers
75 views

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 = ...
4
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3answers
100 views

Make use of relationships on recommendation systems

I have a data set of user rating for movie as user_name, product_name, user_rating and I am using this data to recommend new movie to user (collaborative ...
6
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2answers
88 views

Error on multitask neural nets where all outputs not observed for every example

Let's say I have 2 datasets, each from a set of experiments. Dataset A measures a set of properties X for set S, while dataset B measures properties Y for set T. X and Y are highly correlated, and S ...

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