11-12-2014 04:07 AM
This is part 2 of my question related to discriminant analysis and predictive modelling.
This is the topic i am looking at http://www.kaggle.com/c/forest-cover-type-prediction/
1) For this particular Topic, i wanted to use Discriminant analysis for prediction. What is the advantage or Disadvantage of using DA vs Decision Trees or ordinal logistic regression in this case? i am using SAS EM and i just wanted to get your views on this.
2) The Topic on Kaggle lists variables used within the dataset.
I am trying to understand the importance of these variables in this context. Horizontal_Distance_To_Hydrology - Horz Dist to nearest surface water features Vertical_Distance_To_Hydrology - Vert Dist to nearest surface water features Horizontal_Distance_To_Roadways - Horz Dist to nearest roadway Hillshade_9am (0 to 255 index) - Hillshade index at 9am, summer solstice Hillshade_Noon (0 to 255 index) - Hillshade index at noon, summer solstice Hillshade_3pm (0 to 255 index) - Hillshade index at 3pm, summer solstice Horizontal_Distance_To_Fire_Points - Horz Dist to nearest wildfire ignition point
I am interested to know how the thought process works while selecting a technique in predective modelling.