I have two kind of variables. One kind where the values are continious and ranges from -1 to 5, and the other is boolean (i.e. true or false). For example: V1 V2 V3 V4 V5 V6 0.1 0.4 1 0 -1 3.7 0.4 0.1 2 -1 0 3.7 and V1 V2 V3 0 1 0 0 0 1 I want to make a model for classification, combining this two. Will it be wiser to use the second variable values converting 0 to -1 and 1 to 5, the two extreams. That is, if absent assign the lowest value (i.e. -1) and if present assign the highest value (i.e. 5) Example: V1 V2 V3 V4 V5 V6 V7 V8 V9 0.1 0.4 1 0 -1 3.7 -1 5 -1 0.4 0.1 2 -1 0 3.7 -1 -1 5 Is there is any other way I can merge the two data into one and use for classification. If there any reference that I can go through. Thanking you, anticipating suggestions from you. Regards Now surf faster and smarter ! Check out the new Firefox 3 - Yahoo! Edition http://downloads.yahoo.com/in/firefox/?fr=om_email_firefox [[alternative HTML version deleted]]
I have two kind of variables. One kind where the values are continious and ranges from -1 to 5, and the other is boolean (i.e. true or false). For example: V1 V2 V3 V4 V5 V6 0.1 0.4 1 0 -1 3.7 0.4 0.1 2 -1 0 3.7 and V1 V2 V3 0 1 0 0 0 1 I want to make a model for classification, combining this two. Will it be wiser to use the second variable values converting 0 to -1 and 1 to 5, the two extreams. That is, if absent assign the lowest value (i.e. -1) and if present assign the highest value (i.e. 5) Example: V1 V2 V3 V4 V5 V6 V7 V8 V9 0.1 0.4 1 0 -1 3.7 -1 5 -1 0.4 0.1 2 -1 0 3.7 -1 -1 5 Is there is any other way I can merge the two data into one and use for classification. If there any reference that I can go through. Thanking you, anticipating suggestions from you. Regards Now surf faster and smarter ! Check out the new Firefox 3 - Yahoo! Edition http://downloads.yahoo.com/in/firefox/?fr=om_email_firefox [[alternative HTML version deleted]]
I have two kind of variables. One kind where the values are continuous and ranges from -1 to 5, and the other is boolean (i.e. true or false). For example: V1 V2 V3 V4 V5 V6 0.1 0.4 1 0 -1 3.7 0.4 0.1 2 -1 0 3.7 and V1 V2 V3 0 1 0 0 0 1 I want to make a model for classification, combining this two. Will it be wiser to use the second variable values converting 0 to -1 and 1 to 5, the two extreams. That is, if absent assign the lowest value (i.e. -1) and if present assign the highest value (i.e. 5) Example: V1 V2 V3 V4 V5 V6 V7 V8 V9 0.1 0.4 1 0 -1 3.7 -1 5 -1 0.4 0.1 2 -1 0 3.7 -1 -1 5 Is there is any other way I can merge the two data into one and use for classification. If there any reference that I can go through. Thanking you, anticipating suggestions from you. Regards Bollywood news, movie reviews, film trailers and more! Go to http://in.movies.yahoo.com/ [[alternative HTML version deleted]]