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multiclassPairs v0.4.3 (Release date: 2021-05-16)

minor CRAN fixes

multiclassPairs v0.4.1 (Release date: 2021-01-26)

minor changes

• minor change in rule_based_RandomForest print method
• default of k_range in train_one_vs_rest_TSP set to 10:50 instead of 2:50
• default of genes_altogether and genes_one_vs_rest in sort_rules_RF set to 50 instead of 200
• default of rules_altogether and rules_one_vs_rest in train_RF set to 50 instead of 200
• Update the tutorial with time and accuracy comparisons

multiclassPairs v0.4.0 (Release date: 2020-11-19)

changes

• train_RF has optimized gene_repetition method

multiclassPairs v0.3.1 (Release date: 2020-11-16)

changes

• replace the mode imputation method by kNN method in predict_RF function.
• train_RF now stores the whole binary matrix instead of mode matrix.
• change work-flow figures in the tutorial.
• the predict_RF function can predict matrix with one sample with no error

multiclassPairs v0.3.0 (Release date: 2020-11-02)

changes:

• proximity_matrix_RF replaced cocluster_RF function and it can return and plot the proximity matrix

Bug fixes:

• FIXED: plot_binary_RF does not get the predictions and scores when using as_training=TRUE and top_anno=“platfrom” or “prediction”

multiclassPairs v0.2.2 (Release date: 2020-10-09)

Additions:

• Tutorial is available now.

Minor changes:

• easier access to switchBox disjoint argument in train_one_vs_rest_TSP function.
• Update examples.

Bug fixes:

• plot_binary_TSP when using ExpressionSet as input with no ref or platform.
• passing additional arguments to SB training function by the user.
• printing number of rules in the print function for sorted rules.
• border = NA instead of border = FALSE in plotting functions.
• optimize_RF can handle two classes problems without errors
• num.trees = num.trees missed in ranger for featureNo_altogether slots

multiclassPairs v0.2.1 (Release date: 2020-09-28)

Dependencies:

• Dependency issue solved (switchBox and Biobase packages are installed separately).

Minor changes:

• Update examples.

multiclassPairs v0.2.0 (Release date: 2020-09-24)

Additions:

• additional function summary_genes_RF to summarize genes to rules stats.
• additional function optimize_RF to help in train_RF parameters optimization.

Changes:

• plot_binary_RF now supports when RF model is trained with probability = FALSE.
• plot_binary_RF extracts prediction labels for training data from the classifier object.
• imputation is implemented in predict_RF function.
• NA is not allowed for class and platforms labels.

Optimizations:

• stats for gene repetition in rules are stored in the sorted rules object to make training process faster.

Minor changes:

• Update examples.
• minor bug fixes.

multiclassPairs v0.1.6 (Release date: 2020-09-08)

• first release on CRAN servers

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.