Implement Hoeffding tree for classification using C programming
Budget: $30 – $250 USD
I have data from sensor with two different type of movement. I need to build hoeffding tree model to classify these two classes
Use Hoeffding tree algorithm in order to classify the 3 class (up-down , front-back , pause)
- Min Max scaler
- Selecting the best k features
- Define the number of attributes, classes etc.
- Define the structure for sorting single instance
- Define the structure for sorting single tree node
- Define the function for calculating the entropy of a set of instances
- Define the function of for calculating the information gain of splitting on particular attribute
- Define the function for finding the attribute with maximum information gain
- Define function for creating a new leaf node with a majority class label
- Define function for recursively building a decision tree
o Check if there are no instances
o Check if all the instances have the same class label
o Check if the max depth has been reached
o Check if there are fewer instance than minimum number is required for a split
o Find the attribute with the maximum information gain
o Check if there is no attribute with positive information gain
o Create a new internal node with chosen split attribute
o Create child node for each possible attribute value
o Recursively build child node
o Add the child node to the current node
- Free the memory for the child instances and used attributes arrays
- Return the current node
- Define function for printing a tree
- Define main function read from file
Use Hoeffding tree algorithm in order to classify the 3 class (up-down , front-back , pause)
- Min Max scaler
- Selecting the best k features
- Define the number of attributes, classes etc.
- Define the structure for sorting single instance
- Define the structure for sorting single tree node
- Define the function for calculating the entropy of a set of instances
- Define the function of for calculating the information gain of splitting on particular attribute
- Define the function for finding the attribute with maximum information gain
- Define function for creating a new leaf node with a majority class label
- Define function for recursively building a decision tree
o Check if there are no instances
o Check if all the instances have the same class label
o Check if the max depth has been reached
o Check if there are fewer instance than minimum number is required for a split
o Find the attribute with the maximum information gain
o Check if there is no attribute with positive information gain
o Create a new internal node with chosen split attribute
o Create child node for each possible attribute value
o Recursively build child node
o Add the child node to the current node
- Free the memory for the child instances and used attributes arrays
- Return the current node
- Define function for printing a tree
- Define main function read from file