relates to algorithms that are "trained" by some data set.

learn more… | top users | synonyms

3
votes
2answers
151 views

Clustering algorithm based on distance

So, I have a packaging center A. And I have n points scattered around A. Let's call them i1, i2 ... in. I have a maximum distance threshold, called D. My task is to break those n points into groups ...
0
votes
1answer
57 views

Dynamic gesture recognition with fingertip points

I have built a fairly robust program in c++ which tracks several points on a hand. It accurately quantifies the size of the palm, the center of the palm, and the fingertip locations among other hand ...
2
votes
0answers
101 views

Predicting package delivery schedules

I'm trying to solve the following problem: A delivery man has N packages to deliver, already sorted. He starts the route at start_time, he works until end_time. I have historical data of his ...
2
votes
0answers
100 views

How do I visualise the feature space partitioning in random forest?

I am learning about random forest and found this video https://www.youtube.com/watch?v=gdnIqGbqiYs&list=UUb9svouAi1XHRqlOs8LXbBg very useful. The first 8 minutes explain how to visualise how the ...
2
votes
0answers
35 views

How to use event weights in TMVA ROOT

I'm trying to train and perform classifiers from TMVA. My data set contains event weights besides event data. In the TMVA::Factory there's a method setWeightExpression to specify event weights. What ...
1
vote
0answers
23 views

Create unique buckets for stream of entities based on constraints on the entity attributes

I have stream (magnitude 10s of millions) of entities, say Item which is modeled as below: class Item { String id; Double price; Double profitPercentage; Country originCountry; Country ...
1
vote
0answers
55 views

How is the event model of multinomial naive bayes algorithm right

The event model of multinomial NB is this: P(x1, x2...Xm | y=k) = P(x1 | =k) * P(x2 | y=k) * ...* P(xm | y=k), where x is i'th word in the document. Then we apply it to bag of words model. P = P(x1 ...
1
vote
0answers
174 views

Neural network converges to 0.5 for XoR

I'm coding a neural network in C for an OCR project. Before testing with character recognition, I'm making it learn the XoR operation. Although, the results I'n getting always converges to 0.5 instead ...
1
vote
0answers
118 views

Algorithm to analyse and predict

I'm having a set of data's, say Question, Question's Main Category,Main Category followers, Question's Related Categories,Each Related Categories followers, Whether it got answer in 24hrs [Yes/No] ...
0
votes
0answers
31 views

Is sparsity parameter really useful?

To make a sparse autoencoder,one way is add something to the function we want to minimize,which the further do average activity of hidden units to a sparsity parameter,the bigger your added thing will ...
0
votes
0answers
30 views

What algorithm to use for a specific 'Named Entity Recognition'/'Information extraction' problem

I am trying to write a model that will extract certain details from financial documents. It must be able to extract the; contract start date, contract duration, contract value and all named entities. ...
0
votes
0answers
28 views

How can word lists be used as supervised data in finding the score of the report?

We have got historical reports and we need to find the score (whether report is effective or useful or not) based on supervised learning. While doing the supervised learning process, we have to ...
0
votes
0answers
78 views

Decision making algorithm

I'm currently solving an optimisation problem of my own design, just to experiment and learn a little something. Here's the concept: I have a user that starts at home. The objective of this user is ...
0
votes
0answers
18 views

What are some ways to go about automatically categorizing calendar data?

I'm working on an application that takes as input your calendar data (i.e. the event titles like "Lunch with Barney" and their respective times), and automatically assigns each of them to a category ...
0
votes
0answers
76 views

Will this data mining approach work? Is it a good idea?

I need to extract fields like the document number, date, and invoice amount from a bunch of .csv files, which I believe are referred to as "unstructured text." I have some labeled input files and will ...
-1
votes
0answers
8 views

How to insert log transformed columns into an existing dataframe using column indices (in pandas, python)

How do I insert columns that are log transformed(after doing log transformation of certain variables)of a data frame called 'log_data' back to it's original data frame 'df' using specific column ...