Sympathy
1.4
  • What is Sympathy for Data?
  • What’s new
  • Installation instructions
  • Deprecations
  • Getting started
  • The graphical user interface
  • Typical workflow structure
  • Concepts in Sympathy for Data
  • Machine Learning Concepts
  • Subflows
  • Lambda
  • Using Sympathy from the command line
  • Node writing
  • Advanced node writing
  • Debugging, profiling, and tests
  • How to create reusable nodes
  • Creating a custom data type
  • Using Interactive (Using the Library interactively)
  • Using and supporting Python 3
  • Node interface reference
  • Parameter helper reference
  • Data type APIs
  • Library
    • Internal
    • Sympathy
      • Data
      • Datasources
      • Examples
      • Export
      • Files
      • Filters
      • Imageprocessing
      • List
      • Machinelearning
        • Decision Function
        • Fit
        • Fit Texts
        • Fit Transform
        • Fit Transform Text
        • Inverse Transform
        • Predict
        • Predict Probabilities
        • Score
        • Select Features from Model
        • Transform
        • Transform Text
        • Extract Attributes
        • K-means Clustering
        • Mini-batch K-means Clustering
        • Score Cross Validation
        • Group K-fold Cross Validation
        • K-fold Cross Validation
        • Leave One Group out Cross Validation
        • Simple Train-Test Split
        • Split Data for Cross Validation
        • Stratified K-fold cross validation
        • Time Series K-fold Based Cross Validation
        • Decision Tree Classifier
        • Kernel Principal Component Analysis (KPCA)
        • Principal Component Analysis (PCA)
        • Multi-output classifier
        • Multi-output regressor
        • Voting Classifier
        • Example datasets
        • Export Model
        • Import Model
        • Generate dataset blobs
        • Generate dataset blobs from table
        • Generate classification dataset
        • Isolation Forest
        • Conditional Probabilty from Categories
        • Confusion Matrix
        • Learning Curve
        • ROC from Probabilities
        • Multi-Layer Perceptron Classifier
        • Extract Parameters
        • Parameter Distribution
        • Set Input and Output Names
        • Set Parameters
        • Grid Parameter Search
        • Randomized Parameter Search
        • Simulated Annealing Parameter Search
        • Pipeline
        • Pipeline decomposition
        • Binarizer
        • Categorical Encoder
        • Imputer
        • Label Binarizer
        • Label Encoder
        • Max Abs Scaler
        • Normalizer
        • One-Hot Encoder
        • Polynomial Features
        • Robust Scaler
        • Standard Scaler
        • Random Forest Classifier
        • Kernel Ridge Regression
        • Linear Regression
        • Logistic Regression
        • Epsilon Support Vector Regression
        • One Class SVM
        • Support Vector Classifier
        • Text Count Vectorizer
        • Features to Images
        • Images to Features
      • Random
      • Reporting
      • Selectors
      • Slice
      • Tuple
      • Visualize
    • Plugins
Sympathy
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  • Machinelearning »
  • Grid Parameter Search
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Grid Parameter SearchΒΆ

../../../../_images/hyperparam.svg
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