Closed bzn7 closed 6 years ago
Do you actually have 6000 features?
If yes, your [Column]
should look like this:
[Column("1-1000")] [VectorType(1000)] public float[] param1;
[Column("1001-2000")] [VectorType(1000)] public float[] param2;
// etc.
Have the same issue (ML.NET v0.4). The classifier returns the same prediction (false).
Regarding the post by @bzn7 I consider it makes no difference how many features do a training set have - the answers must be different.
Well, if you have 6000 features, but you read them the way @bzn7 does (994 features appear 6 times each), the learner is going to be severely hampered. My guess was that the model that was learned was trivial, and therefore gave the same prediction all the time.
I think you are incorrect about this one:
I consider it makes no difference how many features do a training set have - the answers must be different.
I would say that if the answers are 'the same all the time', it is unfortunate, but far from uncommon. Here are some factors that can potentially cause this:
DRI RESPONSE: I'm considering this question as answered and intent to close issue within next few days, unless someone have objection.
Do you actually have 6000 features? If yes, your
[Column]
should look like this:[Column("1-1000")] [VectorType(1000)] public float[] param1; [Column("1001-2000")] [VectorType(1000)] public float[] param2; // etc.
I tried to simplify my features and redefined columns as shown. It is working, thank you @Zruty0.
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