Delete RELEASE_NOTES.txt
Kai Staats
GitHub
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2016 07/13 - version 0.9.1.6
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In karoo_gp_base_class.py
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- enabled auto counting of labels (right column) in loaded data (data_y)
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- re-ordered presentation of screen modes, in order of decreasing feedback [i, g, m, s]
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- added argparse to further enhance karoo_gp_server.py as a scriptable tool --FINALLY! :)
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In karoo_gp_main.py
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- removed user query for number of class labels
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- re-ordered presentation of screen modes, in order of decreasing feedback [i, g, m, s]
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In karoo_go_server.py
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- re-ordered presentation of screen modes, in order of decreasing feedback [i, g, m, s]
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- argparse to further enhance karoo_gp_server.py as a scriptable tool
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2016 07/11 - version 0.9.1.5
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In karoo_gp_base_class.py
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- renamed kernel (fitness function) type from 'a' to 'r' for regression
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- renamed all associated variable and methods to match switch from 'abs_value' to 'regression'
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- reorganised validation methods to match order of fitness functions
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- added [other] place holder to validation methods
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In karoo_gp_main.py
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- renamed kernel (fitness function) type from 'a' to 'r' for regression
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- adjusted upper boundary for qty of generations from 1000 to 100
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In karoo_go_server.py
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- renamed kernel (fitness function) type from 'a' to 'r' for regression
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In files/ data_ABS.csv and functions_ABS.csv were rename data_REGRESS.csv and functions_REGRESS.csv accordingly.
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2016 07/10-11 - version 0.9.1.4
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In karoo_gp_base_class.py
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- renamed variable 'tree_depth_max' to 'tree_depth_base'
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- renamed variable 'tree_depth_adj' to 'tree_depth_max'
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- renamed variable 'gp.pop_tree_depth_max' to 'gp.pop_tree_depth_base'
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- enabled 2 children to be produced by each Crossover function
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- extensive testing of Crossover in debug to validate process
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- reduced # of crossover functions per run by 1/2
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- improved on-screen output for all 4 genetic operators
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- removed not-in-use 'accuracy' test
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- added 'Arguments required:' to each method notes
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- edited a number of method notes
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In karoo_gp_main.py
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- renamed variables (according to karoo_gp_base_class.py)
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In karoo_go_server.py
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- renamed variables (according to karoo_gp_base_class.py)
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2016 07/08-09 - version 0.9.1.3
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In karoo_gp_base_class.py
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- added CTRL-C catch to the (pause) menu; removes potential to accidentally kill a run when attempting to
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copy/paste an on-screen function to research notes (use the mouse instead).
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- rebuilt each (pause) menu function for improved exception handling
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- added the new gp.tree_depth_adj user defined variable to branch mutation and crossover, enabling Trees to grow
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beyond their original size which adds opportunity for more complex solutions, as well as the unavoidable bloat
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- reduced complexity of a few lines in both branch mutation and crossover methods
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- tested, tested, tested
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In karoo_gp_main.py
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- added CTRL-C catch to the at-launch user menu.
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- renamed the method gp.fx_karoo_crossover_reproduction() to gp.fx_karoo_crossover()
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- added user input for the new global variable gp.tree_depth_adj
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In karoo_go_server.py
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- added new gp.tree_depth_adj variable
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2016 07/07 - version 0.9.1.2
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In preparation for public launch of Karoo GP, a number of updates are complete or underway.
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The Quick Start Tutorial is being fully revised. A number of corrections were made, but more importantly, all new
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content has been added relevant to preparation of datasets and the use of the Karoo GP Tools accordingly. The genetic
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operators descriptions now feature visuals and revised descriptions, as to many other sections.
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In the karoo_gp/tools/ directory, all scripts have undergone updates, 2 of which now offer automated scaling and a
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user interface that in the original versions were not present, as follows:
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karoo_data_sort.py (formerly karoo_features_sort.py)
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This script now engages the user with a query for the number of class labels and the number of data points (rows)
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for the new, randomly generated subset of the parent dataset. This script is designed to be used prior to
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karoo_normalise.py.
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karoo_normalise.py
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This script now auto-scales to any number of columns and rows (within the limit of your computer's capability),
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and features a text-based user interface. This script is designed to be used following karoo_data_sort.py.
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karoo_multiclassifier.py
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This script functions as before, but with a minor bug fixed in which the final class was mislabeled.
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karoo_iris_plot.py
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This script functions as before, but with improved in-script documentation and cleaner code.
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In development now are a number of updates and improvements to the base_class such that Karoo GP will more readily
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conform to the GP standards, as follows:
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1) Karoo GP currently produces only 1 offspring for each parent, where it should produce 2.
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2) The tree generation method 'Ramped Half/Half', in its current state, produces a 50/50 split of Full and Grow
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methods, not a graduated ramp through all depths.
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3) Karoo GP currently engages a bloat inhibitor, that is, an upper limit on tree depth which is maintained through
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all modes of mutation and crossover. This will become a user defined setting such that it can be adjusted, enabling
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growth of trees beyond the original, user defined limit.
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4) Karoo GP will be made to launch as a single, command-line function with all required parameters included, SciKit
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Learn style.
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2015 12/23 - version 0.9.1.1
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It was discovered that when loading external datasets, Karoo was yet extracting variables (terminals) from the data in
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the files/ directory, according to the selected kernel.
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This is fixed.
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2015 11/04 - version 0.9.1.0
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Initial development of Karoo GP began in February 2015, on a Python-based evolutionary algorithm for an MSc research
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project at the University of Cape Town (UCT) / African Institute for Mathematical Sciences (AIMS) and the Square
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Kilometer Array (SKA). The myriad debug statements evolved into the user interface while the classic Machine Learning
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test cases became the built-in example runs.
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In the course of six months development, the code base grew to become a flexible, easy-to-use platform for Genetic
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Programming.
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Karoo GP has been thoroughly tested on a 40-core server at the Square Kilometer Array offices in Cape Town, South
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Africa, where for one month it chewed through 10,000 rows of data for up to 50 hours without incident. It is proved
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as a fully functional, multi-core workhorse.
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With all development to date conducted locally, this version 0.9 marks the first release to github.
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This initial github release is private, shared with select collaborators only. Please do not distribute any part of
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the code until it is made public.
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Kai Staats
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www.kaistaats.com/research/
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www.kaistaats.com/film/
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