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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1answer
292 views

Different methods for clustering skills in text

Consider a talent pool in which each member has some set of skills. Some of these talent are submitted to orders as potential candidates of which one is selected. It is reasonable to assume that the ...
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4answers
39k views

How to scale an array of signed integers to range from 0 to 1?

I'm using Brain to train a neural network on a feature set that includes both positive and negative values. But Brain requires input values between 0 and 1. What's the best way to normalize my data?
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Where does the sum of squared errors function in neural networks come from?

Training a basic multilayer perceptron neural network boils down to minimizing some kind of error function. Often the sum of squared errors is chosen as a this error function, but where does this ...
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4answers
4k views

How is Data Science related to Machine learning?

I went through this comparison of analytic disciplines and this perspective of machine learning, but I am not finding any answers on the following: How is Data Science related to Machine learning? ...
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1answer
149 views

Ideas for next step of Machine Learning [closed]

I have completely followed the machine learning course on coursera Machine Learning by professor Andrew Ng Now I want to put my knowledge to action. Some ideas that I have include : -Voice ...
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2answers
11k views

Using attributes to classify/cluster user profiles

I have a dataset of users purchasing products from a website. The attributes I have are user id, region(state) of the user, the categories id of product, keywords id of product, keywords id of ...
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1answer
398 views

What is the best technique/algorithm to compare trees changes?

I have a problem I would like to solve using machine learning. I would like to use some sort of classification to know if a just added change in a tree data structure is "good" or is "bad". Let's say ...
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1answer
3k views

Learning time of arrival (ETA) from historical location data of vehicle

I have location data of taxis moving around the city sourced from: Microsoft Research Overall it has around 17million data points. I have converted the data to JSON and filled up mongo. A sample ...
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0answers
74 views

Various algorithms performance in a problem and what can be deduced about data and problem?

HI I am currently trying to apply various algorithms to a classification problem to assess which could be better and then try to fine tune the bests of the first approach. I am a beginner so I use ...
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1answer
162 views

Why are HMMs called linear-chain?

I found in many sources that Hidden Markov Models are linear-chain networks(e.g. in Predicting Structured Data book by MIT). However, as I understand it, HMMs can have any edges in its graph. Even ...
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1answer
99 views

What kind of machine learning algorithm can I use?

I have a data set of tweets regarding vaccines. They have been collected from an API because they have keywords like "flu, measles, MMR, vaccine" etc. I need to find tweets specifically about ...
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1answer
272 views

Ranking Bias in Learning to Rank

Users tend to click on results ranked highly by search engines much more often than those ranked lower. How do you train a search engine using click data / search logs without this bias? I.e. you don'...
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1answer
74 views

When to Perform non-linear dimension reduction

When do we feel need to go through non-linear transformation like kernel PCA ? Please share an example
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1answer
448 views

Finding user similarities within informal data sets

I'm new to all this and am putting together a learning project. I've decided on finding similarities between users in a data set such as http://en.wikipedia.org/wiki/Enron_Corpus. After doing a bit of ...
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3answers
174 views

Datasource for regression model prediction : Machine Learning

I am trying to work using Amazon machine learning, but the data set that I have is small. The model I want to build is for regression based predictions and the domain I am aiming for the data set to ...
3
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1answer
2k views

In Weka, how to draw learning curve evaluated on both test and training set?

This is just for finding overfitting gap. After initial research, I can only find method to draw learning curve using evaluation of test set. However, I could not evaluate on training set and over ...
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1answer
5k views

Where is the cost parameter C in the RBF kernel in SVM?

RBF kernel using SVM depends on two parameters C and gamma. If the equation of the kernel RBF as the following: $K(X,X')= \exp(\gamma||X-X'||^2)$ In the equation I can see where can I use gamma, but ...
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1answer
4k views

Why does logistic regression in Spark and R return different models for the same data?

I've compared the logistic regression models on R (glm) and on Spark (LogisticRegressionWithLBFGS) on a dataset of 390 obs. of ...
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1answer
3k views

Which classification algorithms to try for classifying text data into 300 categories

I have 40000 rows of text data of health care domain. Data has one column for text (2-5 sentences) and one column for its category. I want to classify that into 300 categories. Some categories are ...
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5answers
104k views

What is the “dying ReLU” problem in neural networks?

Referring to the Stanford course notes on Convolutional Neural Networks for Visual Recognition, a paragraph says: "Unfortunately, ReLU units can be fragile during training and can "die". For ...
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4answers
12k views

Dimensionality and Manifold

A commonly heard sentence in unsupervised Machine learning is High dimensional inputs typically live on or near a low dimensional manifold What is a dimension? What is a manifold? What is the ...
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1answer
1k views

Why is the Naive Bayes classifier of sklearn faster than sklearns SVM?

I've used scikit-learn in Python to compare results of naive Bayes and SVM. I've found that naive Bayes is quicker than SVM. Could anyone shed some light on reasons ...
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2answers
4k views

How Mllib in Spark select variables in logistic regression

I have a question about MLlib in Spark.(with Scala) I'm trying to understand how LogisticRegressionWithLBFGS and LogisticRegressionWithSGD work. I usually use SAS or R to do logistic regressions but ...
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2answers
540 views

Understanding text conversion into SVM input [closed]

In Support Vector Machines, when used for sentiment analysis, text gets converted into a set of data points. How does this happen, usually?
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1answer
913 views

What types of features are used in a large-scale click-through rate prediction problem?

Something that I often see in papers (example) about large-scale learning is that click-through rate (CTR) problems can have up to a billion of features for each example. In this Google paper the ...
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2answers
59 views

Pound notation in Summation

I was going through a paper comparing glove and word2vec. I came across the pound notation shown below. What does it mean when used like this? The link for paper is here
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1answer
60 views

Which classifier is efficient in dealing with test query which belongs to no trained class?

Suppose classifier trained with 5 class, and input query content does not belong to any of the trained class data. Naive bayes provides and random class as a result here. Which classifier deals best ...
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1answer
191 views

What are Hybrid Classifiers used in Sentiment Analysis?

What are Hybrid classifiers used for sentiment analysis? How are they built? Please suggest good tutorial/book/link for reference. Also how are they different from other classifiers like SVM and Naive ...
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2answers
673 views

Using clustering and Lasso with cv

I used clustering on my dataset. Now when I'm trying to use a LASSO with cv to predict a response, one of the variables it takes into consideration is which cluster a new point is classified into.(I ...
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0answers
230 views

non-linear optimization for a linear classifier? (scikit-learn)

Using scikit-learn, why would you use bfgs optimization which is non-linear for a linear classifier as logistic regression? I am confused. Does the optimization method finds the optimum of the chosen ...
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1answer
1k views

Optimizing Weka for large data sets

First of all, I hope I'm in the right StackExchange here. If not, apologies! I'm currently working with huge amounts of feature-value vectors. There are millions of these vectors (up to 20 million ...
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0answers
86 views

Prove Reccurrent Neural Network can exhibit oscillatory behavior

I understand how recurrent neural networks work, however I'm trying to build a deep intuitive understanding of their behavior which is difficult for me because they exhibit such complex behaviors. ...
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1answer
2k views

Using EM (Expectation Maximization) algorithm for Training Logistic Regression

Is it possible to learn the weights for a logistic regression classifier using EM (Expectation Maximization)algorithm? Is there any instance reference?
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1answer
114 views

Finding frequencies in a noisy, “uneven” dataset

I'm working on a problem where frequency analysis applies (decomposition of a signal into frequencies, that is), but it's noisy and the samples are unevenly spaced. Specifically: given a list of ...
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1answer
34 views

percentage of confidance on desion trees results

I am looking towards a solution where classification algorithms produce output with some confidence value. but I am confused whether classification algorithms are able to produce results with ...
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1answer
677 views

Difference between OLS(statsmodel) and Scikit Linear Regression

I have a question about two different methods from different libraries which seems doing same job. I am trying to make linear regression model. Here is the code which I using statsmodel library with ...
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2answers
298 views

Complete link clustering

I'm conjecturing that with Complete-linkage clustering two elements from the same cluster will always be closer to each other some other element from another cluster. In more formal terms: Let $C$ ...
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2answers
112 views

Correlations - Get values in the way we want

I have : a matrix X with N lines a vector Y I've computed the Euclidean distance with Y for each line of X. What I get is a vector of distances. What I want is a vector of scores between 0 and 1, ...
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2answers
1k views

Classification of skills based on job ads

I have around 1,000 job ads in the filed of IT (in excel file). I want to find the skills which are mentioned in each of ads. and then find the similar jobs based on skills. My method: I created 12 ...
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4answers
278 views

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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3answers
13k views

How to generate synthetic dataset using machine learning model learnt with original dataset?

Generally, the machine learning model is built on datasets. I'd like to know if there is any way to generate synthetic dataset using such trained machine learning model preserving original dataset ...
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2answers
2k views

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 ...
3
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1answer
3k views

How to create and format an image dataset from scratch for machine learning?

I've only worked with ML with .csv formats. I've worked with image formats too but only premade imagesets (MNIST,etc). If I were to create an imageset from scratch, how are the class labels typically ...
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0answers
184 views

Huge discrepancies in Logistic Regression and SVM using HOG features to identify an Object

I am doing some research on Logistic regression and SVM using different parameters using HOG features. I am facing a bit of problem while understanding each classifier with combination of different ...
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1answer
462 views

Identity covariance matrix, decorrelated data?

Why would you want to decorrelated data? As I am reading about PCA and whitening on image data for DNN, I wonder what is the purpose of achieving the identity covariance matrix in your data is? Is ...
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1answer
412 views

Feature scaling

I am struggling with a conceptual problem related to feature scaling. Let's assume I am building a classifier (e.g., a NN) and let's assume I rely on future scaling for the input features of my model....
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1answer
521 views

Best way to format data for supervised machine learning ranking predictions

I'm fairly new to machine learning, but I'm doing my best to learn as much as possible. I am curious about how predicting athlete performance (runners in particular) in a race of a specific starting ...
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12answers
51k views

Data Science in C (or C++)

I'm an R language programmer. I'm also in the group of people who are considered Data Scientists but who come from academic disciplines other than CS. This works ...
4
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1answer
706 views

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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1answer
622 views

Does pruning a decision tree always make it more general?

If I prune a decision tree, does that make the resulting decision tree always more general than the original decision tree? Are there examples where this is not the case?

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