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.

Filter by
Sorted by
Tagged with
4
votes
2answers
300 views

Detecting Spam using Machine Learning

The most online tutorials like to use a simple example to introduce to machine learning by classify unknown text in spam or not spam. They say that this is a binary-class problem. But why is this a ...
58
votes
10answers
59k views

Machine learning - features engineering from date/time data

What are the common/best practices to handle time data for machine learning application? For example, if in data set there is a column with timestamp of event, such as "2014-05-05", how you can ...
5
votes
1answer
3k views

Neural Networks getting stuck at local optima

I'm training a NN with 8 features and 8000 training examples with a single output (0, 1) using the scipy.optimise CG algorithm and the results are somewhat inconsistent. The goal is to get the NN to ...
3
votes
1answer
94 views

Ranked tag recommendation for university courses

Our system allows an admin to manage a database of university courses. These courses have multiple fields, like the department, a title, and a description. I am adding the ability to add learning ...
4
votes
2answers
358 views

MATLAB Perceptron

I cant seem to figure out why I have a high percentage error. I'm trying to get a perceptron between X1 and X2 which are Gaussian distributed data sets with distinct means and identical co-variances. ...
2
votes
0answers
37 views

making logical inference from a simuation generated data

I have data collected from a computer simulation of football games which seem to have recurring patterns of the following form. if madrid plays arsernal and the match ends under 3 goal, then on their ...
5
votes
1answer
192 views

Rough vs Fuzzy vs Granular Computing

For my Computational Intelligence class, I'm working on classifying short text. One of the papers that I've found makes a lot of use of granular computing, but I'm struggling to find a decent ...
2
votes
4answers
6k views

Small project ideas for Machine Learning [closed]

I need some serious help. I am supposed to implement a project (Non-Existing as of now) for my Machine Learning course. I have no basics in AI or Data mining or Machine learning. I have been searching ...
11
votes
3answers
6k views

Field Aware Factorization Machines

Can anyone explain how field-aware factorization machines (FFM) compare to standard Factorization Machines (FM)? Standard: http://www.ismll.uni-hildesheim.de/pub/pdfs/Rendle2010FM.pdf "Field Aware": ...
6
votes
2answers
1k views

Machine Learning - Where is the difference between one-class, binary-class and multinominal-class classification?

Where is the difference between one-class, binary-class and multinominal-class classification? If I like to classify text in lets say four classes and also want the system to be able to tell me that ...
1
vote
0answers
48 views

Machine Learning - Where is the difference between one-class, binary-class and multinominal-class classification? [duplicate]

Where is the difference between one-class, binary-class and multinominal-class classification? If I like to classify text in lets say four classes and also want the system to be able to tell me that ...
4
votes
9answers
3k views

Python and R good tutorials? [closed]

I would like to learn both Python and R for usage in data science projects. I am currently unemployed, fresh out of university, scouting around for jobs and thought it would be good if I get some ...
3
votes
1answer
4k views

R Script to generate random dataset in 2d space

I want to analyze the effectiveness and efficiency of kernel methods for which I would require 3 different data-set in 2 dimensional space for each of the following cases: BAD_kmeans: The data set ...
2
votes
3answers
335 views

Differences in scoring from PMML model on different platforms

I've built a toy Random Forest model in R (using the German Credit dataset from the caret ...
1
vote
0answers
480 views

Masters thesis topics in Applied probability and Probabilistic models in Machine Learning [closed]

I'm looking for a topic for my masters thesis. Machine learning is my primary domain and I want to work on probabilistic models and applied probability in Machine Learning. Please suggest some ...
2
votes
2answers
326 views

Regression Model for explained model(Details inside)

I am kind of a newbie on machine learning and I would like to ask some questions based on a problem I have . Let's say I have x y z as variable and I have values of these variables as time progresses ...
6
votes
1answer
231 views

Is it possible to identify different queries/questions in sentence?

I want to identifies different queries in sentences. Like - Who is Bill Gates and where he was born? or ...
7
votes
5answers
654 views

Where to start on neural networks

First of all I know the question may be not suitable for the website but I'd really appreciate it if you just gave me some pointers. I'm a 16 years old programmer, I've had experience with many ...
26
votes
3answers
2k views

Why are NLP and Machine Learning communities interested in deep learning?

I hope you can help me, as I have some questions on this topic. I'm new in the field of deep learning, and while I did some tutorials, I can't relate or distinguish concepts from one another.
12
votes
1answer
5k views

Hashing Trick - what actually happens

When ML algorithms, e.g. Vowpal Wabbit or some of the factorization machines winning click through rate competitions (Kaggle), mention that features are 'hashed', what does that actually mean for the ...
6
votes
2answers
8k views

Cosine Similarity for Ratings Recommendations? Why use it?

Lets say I have a database of users who rate different products on a scale of 1-5. Our recommendation engine recommends products to users based on the preferences of other users who are highly similar....
4
votes
2answers
3k views

machine learning algorithms for 2d data?

I'm looking for a supervised learning algorithm that can take 2d data for input and output. As an example of something similar to my data, consider a black image with some sparse white dots. Blur that ...
2
votes
1answer
175 views

Supervised Learning with Necessarily Missing Data

Many discussions of missing data in supervised (and unsupervised) learning deal with various methods of imputation, like mean values or EM. But in some cases the data will be missing as a necessary ...
11
votes
2answers
299 views

How much time do scikit classifiers take to classify?

I am planning to use scikit linear support vector machine (SVM) classifier for text classification on a corpus consisting of 1 million labeled documents. What I am planning to do is, when a user ...
6
votes
3answers
312 views

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 ...
2
votes
1answer
45 views

General programs/libraries for studying user search behavior?

Are there any general open-source programs or libraries (e.g., a Python library) for analyzing user search behavior? By "search behavior", I mean a user's interaction with a search engine, such as ...
6
votes
2answers
7k views

Looking for a strong Phd Topic in Predictive Analytics in the context of Big Data

I'm going to start a Computer Science phd this year and for that I need a research topic. I am interested in Predictive Analytics in the context of Big Data. I am interested by the area of Education (...
3
votes
4answers
2k views

Prerequisites for Data Science [closed]

I'm a Java developer and I want to pursue career in Data Science and machine learning. Please advise me where and how to begin? What subjects and mathematical/statistical skills are required and so ...
2
votes
1answer
388 views

Invariance Property of Vowpal Wabbit Updates - Explaination

One of the discussed nice aspects of the procedure that Vowpal Wabbit uses for updates to sgd pdf is so-called weight invariance, described in the linked as: "Among these updates we mainly focus on ...
14
votes
4answers
730 views

Studying machine learning algorithms: depth of understanding vs. number of algorithms

Recently I was introduced to the field of Data Science (its been 6 months approx), and Ii started the journey with Machine Learning Course by Andrew Ng and post that started working on the Data ...
6
votes
2answers
335 views

Statistical Commute Analysis in Java

I have a rather large commute every day - it ranges between about an hour and about an hour and half of driving. I have been tracking my driving times, and want to continue to do so. I am capturing ...
6
votes
2answers
477 views

Looking for algebras designed to transform time series

I am looking for information on (formal) algebraic systems that can be used to transform time-series - in either a practical or academic context. I hope that there exists (at least one) small, ...
34
votes
4answers
15k views

Quick guide into training highly imbalanced data sets

I have a classification problem with approximately 1000 positive and 10000 negative samples in training set. So this data set is quite unbalanced. Plain random forest is just trying to mark all test ...
9
votes
2answers
451 views

How to build a textual search engine?

I am having an HTML string and want to find out if a word I supply is relevant in that string. Relevancy could be measured based on frequency in the text. An example to illustrate my problem: ...
11
votes
2answers
721 views

Neural net for server monitoring

I'm looking at pybrain for taking server monitor alarms and determining the root cause of a problem. I'm happy with training it using supervised learning and curating the training data sets. The data ...
2
votes
1answer
173 views

Creating obligatory combinations of variables for drawing by random forest

Problem For my machine learning task, I create a set of predictors. Predictors come in "bundles" - multi-dimensional measurements (3 or 4 - dimensional in my case). The hole "bundle" makes sense ...
14
votes
1answer
2k views

Machine learning libraries for Ruby

Are there any machine learning libraries for Ruby that are relatively complete (including a wide variety of algorithms for supervised and unsupervised learning), robustly tested, and well-documented? ...
3
votes
2answers
195 views

non query-based document ranking

We have ~500 biomedical documents each of some 1-2 MB. We want to use a non query-based method to rank the documents in order of their unique content score. I'm calling it "unique content" because our ...
3
votes
0answers
444 views

ANOVA RBF kernel returns very poor results

I was curious about the ANOVA RBF kernel provided by kernlab package available in R. I tested it with a numeric dataSet of 34 input variables and one output variable. For each variable I have 700 ...
13
votes
3answers
7k views

Unstructured text classification

I'm going to classify unstructured text documents, namely web sites of unknown structure. The number of classes to which I am classifying is limited (at this point, I believe there is no more than ...
5
votes
1answer
6k views

Polynomial Kernel Parameters in SVMs

In SVMs the polynomial kernel is defined as: (scale * crossprod(x, y) + offset)^degree How do the scale and offset parameters affect the model and what range should they be in? (intuitively please) ...
9
votes
2answers
3k views

Libraries for Online Machine Learning

I am looking for packages (either in python, R, or a standalone package) to perform online learning to predict stock data. I have found and read about Vowpal Wabbit (https://github.com/JohnLangford/...
6
votes
1answer
191 views

Kappa From Combined Confusion Matrices

I am trying to evaluate and compare several different machine learning models built with different parameters (i.e. downsampling, outlier removal) and different classifiers (i.e. Bayes Net, SVM, ...
-6
votes
2answers
287 views

which programming language has a large library that can do machine learning algorithm, R, matlab or python [closed]

As what I described in the title, we are especially interested in those for dealing with big data----ts efficiency and stability, and used in industry not in experiment or university. Thanks!
13
votes
2answers
4k views

What features are generally used from Parse trees in classification process in NLP?

I am exploring different types of parse tree structures. The two widely known parse tree structures are a) Constituency based parse tree and b) Dependency based parse tree structures. I am able to ...
-3
votes
2answers
1k views

Which one will be the dominating programming language for next 5 years for analytics , machine learning . R or python or SAS [closed]

Which one will be the dominating programming language for next 5 years for analytics , machine learning . R verses python verses SAS. Advantage and disadvantage.
32
votes
4answers
45k views

Do Random Forest overfit?

I have been reading around about Random Forests but I cannot really find a definitive answer about the problem of overfitting. According to the original paper of Breiman, they should not overfit when ...
10
votes
2answers
561 views

implementing temporal difference in chess

I have been developing a chess program which makes use of alpha-beta pruning algorithm and an evaluation function that evaluates positions using the following features namely material, kingsafety, ...
3
votes
0answers
112 views

How can I model open environment in reinforcement learning? [closed]

I'm studying reinforcement learning in order to implement a kind of time series pattern analyzer such as market. The most examples I have seen are based on the maze environment. But in real market ...
3
votes
1answer
215 views

Query similarity: how much data is used in practice?

I recently read Similarity Measures for Short Segments of Text (Metzler et al.). It describes basic methods for measuring query similarity, and in the paper, the data consists of queries and their ...