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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12 votes
9 answers

What are some easy to learn machine-learning applications? [closed]

Being new to machine-learning in general, I'd like to start playing around and see what the possibilities are. I'm curious as to what applications you might recommend that would offer the fastest ...
Steve Kallestad's user avatar
42 votes
10 answers

Can machine learning algorithms predict sports scores or plays?

I have a variety of NFL datasets that I think might make a good side-project, but I haven't done anything with them just yet. Coming to this site made me think of machine learning algorithms and I ...
Steve Kallestad's user avatar
16 votes
2 answers

Where in the workflow should we deal with missing data?

I'm building a workflow for creating machine learning models (in my case, using Python's pandas and sklearn packages) from data ...
Therriault's user avatar
9 votes
3 answers

Human activity recognition using smartphone data set problem

I'm new to this community and hopefully my question will well fit in here. As part of my undergraduate data analytics course I have choose to do the project on human activity recognition using ...
Jakubee's user avatar
  • 401
13 votes
4 answers

Algorithm for generating classification rules

So we have potential for a machine learning application that fits fairly neatly into the traditional problem domain solved by classifiers, i.e., we have a set of attributes describing an item and a "...
super_seabass's user avatar
15 votes
4 answers

How to specify important attributes?

Assume a set of loosely structured data (e.g. Web tables/Linked Open Data), composed of many data sources. There is no common schema followed by the data and each source can use synonym attributes to ...
vefthym's user avatar
  • 503
6 votes
1 answer

Is Data Science just a trend or is a long term concept? [closed]

I see a lot of courses in Data Science emerging in the last 2 years. Even big universities like Stanford and Columbia offers MS specifically in Data Science. But as long as I see, it looks like data ...
Filipe Ferminiano's user avatar
28 votes
6 answers

Machine learning techniques for estimating users' age based on Facebook sites they like

I have a database from my Facebook application and I am trying to use machine learning to estimate users' age based on what Facebook sites they like. There are three crucial characteristics of my ...
Wojciech Walczak's user avatar
15 votes
2 answers

Is there any APIs for crawling abstract of paper?

If I have a very long list of paper names, how could I get abstract of these papers from internet or any database? The paper names are like "Assessment of Utility in Web Mining for the Domain of ...
Alex Gao's user avatar
  • 253
57 votes
8 answers

Why Is Overfitting Bad in Machine Learning?

Logic often states that by overfitting a model, its capacity to generalize is limited, though this might only mean that overfitting stops a model from improving after a certain complexity. Does ...
blunders's user avatar
  • 1,932
17 votes
2 answers

Use liblinear on big data for semantic analysis

I use Libsvm to train data and predict classification on semantic analysis problem. But it has a performance issue on large-scale data, because semantic analysis concerns n-dimension problem. Last ...
Puffin GDI's user avatar
9 votes
1 answer

How can I do simple machine learning without hard-coding behavior? [closed]

I've always been interested in machine learning, but I can't figure out one thing about starting out with a simple "Hello World" example - how can I avoid hard-coding behavior? For example, if I ...
Doorknob's user avatar
  • 215

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