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 determine whether a bad performance is caused by data quality?

I'm using a set of features, says $X_1, X_2, ..., X_m $, to predict a target value $Y$, which is a continuous value from zero to one. At first, I try to use a linear regression model to do the ...
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1answer
347 views

How to compute F1 score?

Recently I read about path ranking algorithm in a paper (source: Knowledge Vault: A Web-Scale Approach to Probabilistic Knowledge Fusion). In this paper was a table (Table 3) with facts and I tried ...
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1answer
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Machine learning for Point Clouds Lidar data

Our main use case is object detection in 3d lidar point clouds i.e. data is not in RGB-D format. We are planning to use CNN for this purpose using theano. Hardware limitations are CPU: 32 GB RAM Intel ...
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Proper way of fighting negative outputs of a regression algorithms where output must be positive all the way

Maybe it is a bit general question. I am trying to solve various regression tasks and I try various algorithms for them. For example, multivariate linear regression or an SVR. I know that the output ...
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290 views

Amplifying a Locality Sensitive Hash

I'm trying to build a cosine locality sensitive hash so I can find candidate similar pairs of items without having to compare every possible pair. I have it basically working, but most of the pairs in ...
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1answer
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Pre-processing (center, scale, impute) among training sets (different forms) and the test set - what is a good approach?

I am currently working on a multi-class classification problem with a large training set. However, it has some specific characteristics, which induced me to experiment with it, resulting in few ...
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3answers
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Help regarding NER in NLTK

I have been working in NLTK for a while using Python. The problem I am facing is that their is no help available on training NER in NLTK with my custom data. They have used MaxEnt and trained it on ...
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1answer
790 views

Can 2 dimensional input be applied to SVM? [closed]

When considering Support Vector Machine, in an take in multiple inputs. Can each of these inputs be a vector?? What i am trying to say is, can the input be a 2 dimensional vector??
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9answers
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Machine learning toolkit for Excel

Do you know of any machine learning add-ins that I could use within Excel? For example I would like to be able to select a range of data and use that for training purposes and then use another sheet ...
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1answer
2k views

How to extract features and classify alert emails coming from monitoring tools into proper category?

My company provides managed services to a lot of its clients. Our customers typically uses following monitoring tools to monitor their servers/webapps: OpsView Nagios Pingdom Custom shell scripts ...
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4answers
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How to learn a classifier from a dataset with high imbalance

What are the most useful techniques for learning a binary classifier from a dataset with a high degree of imbalance (i.e., a dataset with the "target" class being much rarer than the "background" ...
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High-dimensional data: What are useful techniques to know?

Due to various curses of dimensionality, the accuracy and speed of many of the common predictive techniques degrade on high dimensional data. What are some of the most useful techniques/tricks/...
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What happens when we train a linear SVM on non-linearly separable data?

What happens when we train a basic support vector machine (linear kernel and no soft-margin) on non-linearly separable data? The optimisation problem is not feasible, so what does the minimisation ...
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Could someone please offer me some guidance on some kind of particular, SPECIFIC project that I could attemp, to “get my feet wet, so to speak” [closed]

I am COMPLETELY new to the field of Data Science, mainly because every employer I have worked for, simply COULDN'T sell any customers anything that would use techniques learned in this field. Of ...
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When to use what - Machine Learning [closed]

Recently in a Machine Learning class from professor Oriol Pujol at UPC/Barcelona he described the most common algorithms, principles and concepts to use for a wide range of machine learning related ...
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What is the difference between feature generation and feature extraction?

Can anybody tell me what the purpose of feature generation is? And why feature space enrichment is needed before classifying an image? Is it a necessary step? Is there any method to enrich feature ...
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1answer
200 views

What are the current killing machine learning methods? [closed]

I was wondering whether we could list machine learning winning methods to apply in many fields of interest: NLP, image, vision, medical, deep package inspection, etc. I mean, if someone will get ...
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2answers
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Probability distribution in input-output pairs

This question might sound silly. But I have been wondering why do we assume that there is a hidden probability distribution between input-output pairs in machine learning setup ? For example, if we ...
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2answers
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Generate tags for live chat transcripts

I'm wondering if there's a way to automatically generate a list of tags for live chat transcripts without domain knowledge. I've tried applying NLP chunking to the chat transcripts and keep only the ...
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4answers
906 views

Determine highly correlated segments

Given a dataset that has a binary (0/1) dependent variable and a large collection of continuous and categorical independent variables, is there a process and ideally a R package that can find ...
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Aspect based sentiment analysis using machine learning approach

I am very new in machine learning. I have annotated data with category, aspect, opinion word and sentiment. for example, for the bellow text "The apple was really tasty" I have category->food, ...
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1answer
439 views

Learning cost function for linear regression

(Me: Never learned calculus or advanced math and I started Stanford openclasses for machine learning. I know basic matrix calculations.) One chapter of my course is about cost function. I have been ...
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1answer
170 views

Correlation threshold for Neural Network features selection

I'm trying to do a correlation analysis between inputs and outputs inspecting the data in order to understand which input variables to include. What could be a threshold in the correlation value to ...
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1answer
85 views

normalize identification values properly

I'm building a neural network to analyze a business' sales. I'm normalizing all input values to the range {0,1}. I'm struggling with the day of the week column. ...
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1answer
118 views

Compare Neural Network generalization results

I'm trying to develop my neural network with both early stopping and bayesian regularization (matlab implementation, lm algorithm is used for both). Since in bayesian regularization I have not the ...
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1answer
465 views

Are Correlithm Objects used for anything in the industry?

This refers to a system described in a book by Nick Lawrence titled "Correlithm Object Technology". The author coined the term "correlithm" as a combination of "correlation" and "algorithm". The ...
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1answer
159 views

How to model this “un predicatability” problem?

Imagine modeling the "input(plaintext) - output(ciphertext)" pairs of an encryption algorithm as a data science problem. Very informally, the strength of an encryption scheme is measured by the ...
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0answers
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How to transform one graph to a spectrum?

Recently, I studied a paper called "What Does Your Chair Know About Your Stress Level? It can be download at the link below. http://www.barnrich.ch/wiki/data/media/pub/...
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1answer
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predict with Multinomial Logistic Regression

If I execute the following code I have no problem: ...
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2answers
473 views

How to apply AdaBoost to more “complex” (non-binary) classifications/data fitting?

In this article, Chris McKinlay says he used AdaBoost to choose the proper "importances" of questions he answered on okcupid. If you haven't read and don't want to read the article, or are unfamiliar ...
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2answers
486 views

Neural Network Hidden Neuron Selection Strategy

I'm trying to determine what is the best number of hidden neurons for my MATLAB neural network. I was thinking to adopt the following strategy: Loop for some values of hidden neurons, e.g. 1 to 40; ...
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2answers
51 views

How are the findings learnt from the data set are generalized compared to Statistics?

I am new to data science/ machine learning world. I know that in Statistics we assume that a certain event/ process has some particular distribution and the samples of that random process are part of ...
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3answers
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Bayesian Decision Tree

I was looking to learn about Bayesian theory in decision tree and how it avoids overfitting but couldn't find any tutorials for someone just starting. Do you know any resources to learn about it?
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1answer
618 views

What does 'contextual' mean in 'contextual bandits'?

I recently read a lot about the n-armed bandit problem and its solution with various algorithms, for example for webscale content optimization. Some discussions were referring to 'contextual bandits', ...
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Improving Naive Bayes accuracy for text classification

I am performing document (text) classification on the category of websites, and use the website content (tokenized, stemmed and lowercased). My problem is that I have an over-represented category ...
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1answer
2k views

Machine Learning for hedging/ portfolio optimization?

With increasingly sophisticated methods that work on large scale datasets, financial applications are obvious. I am aware of machine learning being employed on financial services to detect fraud and ...
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1answer
17k views

How does the naive Bayes classifier handle missing data in training?

Naive Bayes apparently handles missing data differently, depending on whether they exist in training or testing/classification instances. When classifying instances, the attribute with the missing ...
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1answer
129 views

Choice of weights for the Laplacian Eigenmaps algorithm

In his thesis (section 2.3.3) Belkin uses the heat equation to derive an approximation for $\mathcal{L}f$: $$\mathcal{L}f(x_i)\approx \frac{1}{t}\Big(f(x_i)-\alpha \sum_{x_j, ||x_i-x_j||<\epsilon}...
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3answers
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What cost function and penalty are suitable for imbalanced datasets?

For an imbalanced data set, is it better to choose an L1 or L2 regularization? Is there a cost function more suitable for imbalanced datasets to improve the model score (...
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2answers
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What are the best practices to anonymize user names in data?

I'm working on a project which asks fellow students to share their original text data for further analysis using data mining techniques, and, I think it would be appropriate to anonymize student names ...
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1answer
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Exporting R model to OpenCV's Machine Learning Library

I'm wonder if it's possible to export a model trained in R, to OpenCV's Machine Learning (ML) library format? The latter appears to save/read models in XML/YAML, whereas the former might be exportable ...
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1answer
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Multiple labels in supervised learning algorithm

I have a corpus of text with a corresponding topics. For example "A rapper Tupac was shot in LA" and it was labelled as ...
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Visualizing deep neural network training

I'm trying to find an equivalent of Hinton Diagrams for multilayer networks to plot the weights during training. The trained network is somewhat similar to a Deep SRN, i.e. it has a high number of ...
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3answers
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kNN - what happens if more than K observation have the same distance to the centroid of the cluster

EDIT It was pointed out in the Answers-section that I am confusing k-means and kNN. Indeed I was thinking about kNN but wrote k-means since I'm still new to this topic and confuse the terms quite ...
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6answers
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Deep learning basics

I am looking for a paper detailing the very basics of deep learning. Ideally like the Andrew Ng course for deep learning. Do you know where I can find this ?
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1answer
550 views

Assign new point to a class using spectral clustering

Say I used spectral clustering to cluster a data-set $D$ of points $X_0 - X_n$ into a number $C$ of clusters. How can I efficiently assign a new single point $X_{n+1}$ to his convenient cluster? Do I ...
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1answer
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Machine Learning & 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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1answer
145 views

Linear combination of weak estimators over fuzzy classifiers?

Having: a set of soft fuzzy classifiers (classification onto overlapping sets) $C_i(x) \to [0,1]$; a corresponding set of weak estimators $R_i(z)$ of the form $R_i(z) = \mathit{EX}(y\mid z)$. The ...
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5answers
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What would be a good way to use clustering for outlier detection?

For simplicity let's assume the feature space is the XY plane.
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Item based and user based recommendation difference in Mahout

I would like to know how exactly mahout user based and item based recommendation differ from each other. It defines that User-based: Recommend items by finding similar users. This is often harder to ...