- How do I choose a Pretrained model?
- How do you validate a deep learning model?
- How do I know which model to use?
- Which regression model is best?
- What is the basic selection model?
- How do I know which ML model to use?
- How can I improve my deep learning model?
- Which algorithm is best for prediction?
- What is a good R squared value?

## How do I choose a Pretrained model?

You always want to go for the smallest model that works well for your data.

Up until earlier this year, people usually start with VGG16 or VGG19, but Resnet is also a great choice for fine tuning.

Start with Resnet18, then to Resnet34 and Resnet50.

You could also try the newer models in ResNext or Nascent nets..

## How do you validate a deep learning model?

The following methods for validation will be demonstrated:Train/test split.k-Fold Cross-Validation.Leave-one-out Cross-Validation.Leave-one-group-out Cross-Validation.Nested Cross-Validation.Time-series Cross-Validation.Wilcoxon signed-rank test.McNemar’s test.More items…

## How do I know which model to use?

How to Choose a Machine Learning Model – Some GuidelinesCollect data.Check for anomalies, missing data and clean the data.Perform statistical analysis and initial visualization.Build models.Check the accuracy.Present the results.

## Which regression model is best?

Statistical Methods for Finding the Best Regression ModelAdjusted R-squared and Predicted R-squared: Generally, you choose the models that have higher adjusted and predicted R-squared values. … P-values for the predictors: In regression, low p-values indicate terms that are statistically significant.More items…•

## What is the basic selection model?

Model selection is the task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of data is considered. … Given candidate models of similar predictive or explanatory power, the simplest model is most likely to be the best choice (Occam’s razor).

## How do I know which ML model to use?

Do you know how to choose the right machine learning algorithm among 7 different types?1-Categorize the problem. … 2-Understand Your Data. … Analyze the Data. … Process the data. … Transform the data. … 3-Find the available algorithms. … 4-Implement machine learning algorithms. … 5-Optimize hyperparameters.More items…

## How can I improve my deep learning model?

Increase model capacityIncrease model capacity.To increase the capacity, we add layers and nodes to a deep network (DN) gradually. … The tuning process is more empirical than theoretical. … Model & dataset design changes.Dataset collection & cleanup.Data augmentation.Semi-supervised learning.Learning rate tuning.More items…

## Which algorithm is best for prediction?

Naive Bayes is a simple but surprisingly powerful algorithm for predictive modeling. The model is comprised of two types of probabilities that can be calculated directly from your training data: 1) The probability of each class; and 2) The conditional probability for each class given each x value.

## What is a good R squared value?

Any study that attempts to predict human behavior will tend to have R-squared values less than 50%. However, if you analyze a physical process and have very good measurements, you might expect R-squared values over 90%.