Machine Learning
Features
- learn from a training set to classify/categorize data examples
- predict the class/category of unfamiliar (novel) data examples based on what is learned
- evaluate the training accuracy and effectiveness of different machine learning models on your training set
- example applications:
- train & predict membrane transport based on pharmacological profiles
- train & predict disease of patients based on physiological parameters
- train & predict behaviour based on physiological parameters & preferences
- etc...
- Author: Mingyuan Li
System Requirements
Operating System: |
Windows, Mac OS, Linux, or Solaris |
Disk Space Usage: |
7 MB |
RAM: |
depends on your training/test/data set size |
Java: |
Java Runtime Environment Version 8u45 or above |
Screenshots
Click on an image below to see the image in its full size.
Shortcut: you can use the left and right arrow keys to traverse through the screenshots :)
Specifications
Training set |
- each data attribute must be separated by commas "," (use .csv file type)
- each input example must begin from a new line
- class/category of data: the value in the first column (or the first value in each line); this can contain alphanumeric characters
- training data: (starting from second column) must be only numbers. (empty values are currently treated as 0, but this can be changed)
- hint: you can use numbers to replace words (ie. denote 1 as male and 0 as female, etc.)
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View sample training data
Download sample training data
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Test set |
- used to test the accuracy/effectiveness of each machine learning model on your training set
- the test set needs to be formatted the exact same way as training set
- hint: you can split your training set into training set and test set
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View sample test data
Download sample test data
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Data set |
- this data set contains only data (numbers only), without classes/categories
- the machine learning program will classify/categorize your data based on what is learned from training set
- hint: this data set should have 1 less column than your training/test set
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View sample data
Download sample data
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click here to view output for the sample inputs
Information on example data
- the sample data provided trains the program to determine what a person might do on a particular day (soccer, ski, or stay in doors) based on the day's temperature, wind speed, and precipitation.
- the 1st column in training and test set is what a person would do on a particular day
- the 1st data attribute (2nd column in training and test set; OR 1st column in data set) is the temperature (°C) of a particular day
- the 2nd data attribute (3rd column in training and test set; OR 2nd column in data set) is the wind speed (km/hr) of a particular day
- the 3rd data attribute (4th column in training and test set; OR 3rd column in data set) is whether it is raining/snowing or not
(0 = no precipitation, 1 = raining, 2 = snowing)
- all files are of .csv format
- note: data of the same class/category do not have to be grouped together in training and test sets
Download
This software is no longer available for download. Please email me at mingyuanli.5000[(at)]gmail.com if you wish to have a copy of the software.