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Calcimator

Training Data Size Calculator

Estimate minimum dataset size needed for machine learning models based on features, complexity, and accuracy targets.

Inputs

Results

Minimum Total Samples

2,890

Samples per Class

578

Est. Collection Time96 hrs
How to Use This Calculator
  1. Enter Number of Features, Model Complexity, and Linear/Logistic.
  2. Set Tree/Ensemble, Deep Neural Network, and Target Accuracy (%).
  3. Adjust Number of Classes as needed.
  4. Review Minimum Total Samples and Samples per Class.
  5. Use Est. Collection Time (hrs) to inform your decision.

How the result changes with Target Accuracy (%)

Target Accuracy (%)Minimum Total SamplesSamples per Class
64%2,080416
74%2,035407
85%2,500500
95%3,390678

What each input means

Number of Features
Number of input features/variables in the dataset
Model Complexity
More complex models need significantly more training data
Target Accuracy (%)
Desired model accuracy — higher targets require exponentially more data
Number of Classes
Number of output classes for classification (2 for binary)

How this is calculated

Worked example, using the default values

  1. Identify Input Parameters
    4 parameters
    Number of Features = 20, Model Complexity = 1, Target Accuracy (%) = 90, Number of Classes = 5 = 4 input(s) provided
  2. Calculate Minimum Total Samples
    Minimum Total Samples
    2890 = 2890
  3. Calculate Samples per Class
    Samples per Class
    578 = 578
  4. Calculate Est. Collection Time
    Est. Collection Time
    96 = 96

Engine last updated . Checked against 2 independently-derived tests — how we verify calculators.

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