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
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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
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	[[alternative HTML version deleted]]