From 1e4b4f3e8289b2500ab25990b0e0597cdca7b00c Mon Sep 17 00:00:00 2001 From: Jason Sakellariou Date: Tue, 2 May 2023 10:57:29 +0300 Subject: [PATCH] update algorithm descriptions and labels Descriptions and labels copied from https://redmine.hbpmip.link/issues/728 --- .../mip-algorithms/CALIBRATION_BELT/properties.json | 2 +- .../src/mip-algorithms/CART/properties.json | 12 ++++++------ .../src/mip-algorithms/ID3/properties.json | 12 ++++++------ .../src/mip-algorithms/KMEANS/properties.json | 6 +++--- 4 files changed, 16 insertions(+), 16 deletions(-) diff --git a/Exareme-Docker/src/mip-algorithms/CALIBRATION_BELT/properties.json b/Exareme-Docker/src/mip-algorithms/CALIBRATION_BELT/properties.json index 1b4318e4b..09b1c81a3 100644 --- a/Exareme-Docker/src/mip-algorithms/CALIBRATION_BELT/properties.json +++ b/Exareme-Docker/src/mip-algorithms/CALIBRATION_BELT/properties.json @@ -21,7 +21,7 @@ { "name": "y", "label": "y", - "desc": "Observed dichotomous outcomes.", + "desc": "Observed dichotomous outcome.", "type": "column", "columnValuesSQLType": "text, integer", "columnValuesIsCategorical": "true", diff --git a/Exareme-Docker/src/mip-algorithms/CART/properties.json b/Exareme-Docker/src/mip-algorithms/CART/properties.json index 201527f25..72112ec0d 100644 --- a/Exareme-Docker/src/mip-algorithms/CART/properties.json +++ b/Exareme-Docker/src/mip-algorithms/CART/properties.json @@ -1,12 +1,12 @@ { "name": "CART", - "desc": "CART, used to generate a decision tree from a dataset", - "label": "CART", + "desc": "Decision tree-based algorithm that splits the data into smaller subsets based on the feature that provides the most information gain, and then builds the tree recursively on the smaller subsets.", + "label": "Classification and Regression Trees (CART)", "type": "python_iterative", "parameters": [{ "name": "x", - "label": "x", - "desc": "Independent variables: A list of variables from database.", + "label": "Covariate (independent)", + "desc": "One or more variables", "type": "column", "columnValuesSQLType": "real, integer", "columnValuesIsCategorical": "", @@ -17,8 +17,8 @@ "valueType": "string" }, { "name": "y", - "label": "y", - "desc": "Dependent variable: A variable from database.", + "label": "Variable (dependent)", + "desc": "A unique variable", "type": "column", "columnValuesSQLType": "real, integer, text", "columnValuesIsCategorical": "", diff --git a/Exareme-Docker/src/mip-algorithms/ID3/properties.json b/Exareme-Docker/src/mip-algorithms/ID3/properties.json index e7120e5a5..1f48c58c4 100644 --- a/Exareme-Docker/src/mip-algorithms/ID3/properties.json +++ b/Exareme-Docker/src/mip-algorithms/ID3/properties.json @@ -1,12 +1,12 @@ { "name": "ID3", - "desc": "Iterative Dichotomiser 3, used to generate a decision tree from a dataset", - "label": "ID3", + "desc": "Decision tree-based algorithm that builds the tree by choosing the feature with the highest information gain at each step.", + "label": "Iterative Dichotomiser 3 (ID3)", "type": "iterative", "parameters": [{ "name": "x", - "label": "x", - "desc": "Independent variables: A list of categorical variables from database.", + "label": "Covariate (independent)", + "desc": "One or more categorical variables", "type": "column", "columnValuesSQLType": "text,integer", "columnValuesIsCategorical": "true", @@ -17,8 +17,8 @@ "valueType": "string" }, { "name": "y", - "label": "y", - "desc": "Dependent variable: A categorical variable from database.", + "label": "Variable (dependent)", + "desc": "A unique categorical variable", "type": "column", "columnValuesSQLType": "text,integer", "columnValuesIsCategorical": "true", diff --git a/Exareme-Docker/src/mip-algorithms/KMEANS/properties.json b/Exareme-Docker/src/mip-algorithms/KMEANS/properties.json index 3cb3c2615..10346998c 100644 --- a/Exareme-Docker/src/mip-algorithms/KMEANS/properties.json +++ b/Exareme-Docker/src/mip-algorithms/KMEANS/properties.json @@ -1,12 +1,12 @@ { "name": "KMEANS", - "desc": "KMEANS_accurate", + "desc": "Unsupervised learning algorithm that partitions a set of data points into k clusters, where k is a user-defined parameter. The algorithm iteratively updates the centroids of each cluster until convergence.", "label": "k-Means Clustering", "type": "iterative", "parameters": [{ "name": "y", - "label": "y", - "desc": "A list of real/integer variables from database.", + "label": "Variables (independent)", + "desc": "A list of continuous variables", "type": "column", "columnValuesSQLType": "real,integer", "columnValuesIsCategorical": "false",