Welcome,
Guest
. Please
login
or
register
.
Did you miss your
activation email?
Home
Help
Search
Login
Register
RapidMiner
RapidMiner Forum
»
RapidMiner Studio
»
Data Mining / ETL / BI Processes
»
Which Learning Algorithm?
Pages: [
1
]
« previous
next »
Print
Author
Topic: Which Learning Algorithm? (Read 443 times)
Crow
Newbie
Posts: 1
Which Learning Algorithm?
«
on:
May 09, 2013, 08:19:17 AM »
I have thousands of samples consisting of two floating point numbers within the range 0 to 1 that associate (result) to a binary outcome. I want to train a learning algorithm with these samples in order to predict the probability that a given sample not found in the training set would produce a true (1) outcome. If I consider each sample to be composed of two random variables (X and Y), then I know that as X goes towards 1, the outcome approaches 1 (true). As X -> 0, the outcome approaches (0) false. The same applies to Y, but the relationship is not linear. In some cases, a sample in the training set might be present more than once, but have opposite outcomes. So the trained algorithm would produce a result interpreted as the probability that a given sample has a true (1) outcome. Can anyone recommend a good algorithm for this problem?
Logged
Pages: [
1
]
Print
« previous
next »
Jump to:
Please select a destination:
-----------------------------
General Community
-----------------------------
=> News and Updates
=> Data Mining
=> Chit Chat
-----------------------------
RapidMiner Studio
-----------------------------
=> Getting Started
=> Data Mining / ETL / BI Processes
=> Problems and Support
=> Feature Requests
=> Development
-----------------------------
RapidMiner Server (formerly RapidAnalytics)
-----------------------------
=> Getting Started
=> Applications and Integration
Loading...