About the Data

The training dataset contains 250k observations with 54 cartographic variables excluding the target variable (i.e. Cover_Type).

Data Description

Name Description

Elevation Elevation in meters

Aspect Aspect in degrees azimuth

Slope Slope in degrees

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 Hillshade index at 9am, summer solstice

Hillshade_Noon Hillshade index at noon, summer soltice

Hillshade_3pm Hillshade index at 3pm, summer solstice

Horizontal_Distance_To_Fire_Points Horz Dist to nearest wildfire ignition points

Wilderness_Area (4 binary columns) Wilderness area designation

Soil_Type (40 binary columns) Soil Type designation

Cover_Type (7 types) Forest Cover Type designation

Note: You can read the downloaded dataset from the 'Data' section using pandas read_csv() function.

Saving Prediction File & Sample Submission

You can find more details on how to save a prediction file here: https://discuss.dphi.tech/t/how-to-submit-predictions/548

Sample submission: You should submit a CSV file with a header row and the sample submission can be found below:

prediction

7

6

5

6

5

3

2

4

.

.

.

.

Etc.

Note that the header name should be ‘prediction’ else it will throw an evaluation error.

Acknowledgement

This dataset is sourced from UCI Machine Learning Repository.

Original owners of database:

Remote Sensing and GIS Program

Department of Forest Sciences

College of Natural Resources

Colorado State University

Fort Collins, CO 80523

(contact Jock A. Blackard, jblackard 'at' fs.fed.us

or Dr. Denis J. Dean, denis.dean 'at' utdallas.edu)

Data Sprint #29: Forest Cover Type

Challenge Starts

Registration Ends

Challenge Ends