CODEWITHSUNDEEP
machine-learningdata-miningtime-seriesclassificationprediction
Basmah
Basmah

Reputation: 899

Popular Items suggestion - Time Sensitive Data - Data Mining

I am a newbee in the field of data mining. I am working on very interesting Data Minign problem. Data description is as follows:

Data is time sensitive. Item attributes are dependent on time factor as well as its class label. I am grouping weekly data as one instance of training or test record. Each week, some of the item attributes may change along with its Popularity(i.e. Class label).

Some sample data as below:

IsBestPicture,MovieID,YearOfRelease,WeekYear,IsBestDirector,IsBestActor,IsBestAc‌​tress,NumberOfNominations,NumberOfAwards,..,Label
-------------------------------------------------
0_1,60000161,2000,1,9-00,0,0,0,0,0,0,0
0_1,60004480,2001,22,19-02,1,0,0,11,3,0,0
0_1,60000161,2000,5,13-00,0,0,0,0,0,0,1
0_1,60000161,2000,6,14-00,0,0,0,0,0,0,0
0_1,60000161,2000,11,19-00,0,0,0,0,0,0,1

My research advisor suggested to use Naive Bayes algorithm which can adapt such dynamic data that is changing with time.

I am using data from 2000-2004 as Training an 2005 as Testing. If i include Week-Year attribute in my items data set, then it will cause 0 probability in Naive Bayes. Is it ok to omit this attribute from my data set after organizing my data in chronological order?

Moreover, how to adapt my model as i read new test cases ? as the new test cases might cause change in Class label ?

Upvotes: 0

Views: 178

Answers (1)

William M-B
William M-B

Reputation: 321

Can you provide a little more insight into your methods? For instance, are you using R, SPSS, Python, SQL Server 2008R2, or RapidMiner 5.2? And if you can include a very small (3-4 row segment) of some of your data, that would help people figure out how to tackle this.

One immediate approach to get an idea of what you are looking at would be to do a Random Forest/Decision Tree and K-Means clustering in order to determine common seperation points in the data. Have you begun by a quick glance at the data's histograms, averages, and outliers?

Upvotes: 0

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