ISIDA/ModelAnalyzer


    ModelAnalyzerC

    This software uses a text file containing predictions of a classification models. The text file shall be organized as follows :

    • if a line starts with a "#", it is a command or a comment if it is not interpreted
    • possible commands are :
      • #SDF sdfile.sdf
      • #Classes  : the number of classes of the classifications problem. For a binary classification, this number is 2.
      • #Predictions  : the number of column containing classification outputs. If only the file concerns only one model, the number value is 1.
      • #Weights ... : This line contains an array of values, at least one per classification outputs. These values are used to weight the vote of classification models for a vote.
    • A data lines shall be structures as follows :
      • First column is the ID of the sample
      • Second column, the reference/experimental value
      • Next #Predictions columns are the actual class assignments by the model
      • Next #Predictions columns are real values interpreted as a confidence score of the class assignment. One value per model.

    If an SDF is provided, the compounds are supposed to follow the same order in the SDF file as referenced by the IDs. The ID of the first molecule shall be 1 and so on.

    The software supports files ".out" which are expected to be Weka outputs containing class assignment for each instances in CSV format.

    Linux version : download

    Mac version (Yosemite) : download

    Windows : download


    ModelAnalyzerR

    This software uses a text file containing predictions of a regression models. The text file shall be organized as follows :

    • if a line starts with a "#", it is a command or a comment if it is not interpreted
    • possible commands are :
      • #SDF sdfile.sdf
      • #Predictions  : the number of column containing classification outputs. If only the file concerns only one model, the number value is 1.
      • #Weights ... : This line contains an array of values, at least one per classification outputs. These values are used to weight the vote of classification models for a vote.
    • A data lines shall be structures as follows :
      • First column is the ID of the sample
      • Second column, the reference/experimental value
      • Next #Predictions columns are the actual estimates of the model
      • Next #Predictions columns are real values interpreted as a confidence score of the estimates. One value per model.

    If an SDF is provided, the compounds are supposed to follow the same order in the SDF file as referenced by the IDs. The ID of the first molecule shall be 1 and so on.

    The software supports files ".out" which are expected to be Weka outputs containing estimates for each instances in CSV format.

    Linux version : download

    Mac version (Yosemite) : download

    Windows : download