Classification model for movie rating prediction I am somewhat new to data mining, and I am working on a classification model for movie rating prediction. 
I have collected data sets from IMDB, and I am planning to use a decision trees and nearest neighbor approaches for my model. I would like to know which freely available data mining tool could provide the functionality that I require. 
 A: Weka is a free and open-source machine-learning suite of tools.  They have a GUI as well as an API to call from your Java code if you want.
They have many classification algorithms including several decision tree algorithms.  These are available in the UI.  Nearest neighbors are a bit more tricky and it seems you have to use the API directly.
I think Rapid Miner probably supports this type of thing, but I haven't used it for such purposes before.
You might also consider R, but that might require getting your hands a little dirtier.
Note that Netflix has done a ton of work in movie rating classification.  Several years ago they offered a $1 million prize to the group that could improve their classification the most.  You might be interested in reading how various teams approached that problem.
A: Hein, 
there are a lot of tools and libs with the functionality available.
Which to choose depends whether you would like to use a gui for your work or if you would like to embed it in some other program.
Standalone Data mining tools (there are ohters like WEKA with Java interface):


*

*Rapid Miner

*Orange

*Rattle gui for R

*KNIME


Text based:


*

*GNU R


Libs:


*

*Scikit for Python

*Mahout on Hadoop


If you know a programming language well enough I would use a lib for that language or give R a try. If not you may try one of the tools with gui.
A tree example in R:
# we are using the iris dataset
data(iris)

# for our tree based model we use the rpart package
# to download it type install.packages("rpart")
library(rpart)

# Building the tree
fit <- rpart(Species ~ Petal.Length + Petal.Width, method="class", data=iris)

# Plot the tree
plot(fit)
text(fit)

As suggested the analysis with R requires you to code yourself, but you will find a package for most classification tasks which will work out of the box. An overview can be found here Machine Learning Task View
To get started with RapidMinder you should have a look at Youtube. There are some screencasts, even for decision trees.
A: May be... WEKA?
http://www.cs.waikato.ac.nz/ml/weka/
