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Logistic Regression FeatureCloud App

Description

A Logistic Regression FeautureCloud app, allowing a federated computation of the logistic regression algorithm.

Input

  • train.csv containing the local training data (columns: features; rows: samples)
  • test.csv containing the local test data

Output

  • pred.csv containing the predicted value
  • prob.csv containing the predicted probability
  • train.csv containing the local training data
  • test.csv containing the local test data

Workflows

Can be combined with the following apps:

  • Pre: Cross Validation, Normalization, Feature Selection
  • Post: Classification Evaluation

Config

Use the config file to customize your training. Just upload it together with your training data as config.yml

fc_logistic_regression
  input:
    train: "train.csv"
    test: "test.csv"
  output:
    pred: "pred.csv"
    test: "test.csv"
  format:
    sep: ","
    label: "Class
  split:
    mode: directory # directory if cross validation was used before, else file
    dir: data # data if cross validation app was used before, else .
  algo:
    max_iterations: 10000 # Maximum number of iterations

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