It stands for the Scalable Parallelizable Induction of Decision Tree algorithm. It was introduced by Shafer et al in 1996. It is a fast, scalable decision tree classifier. It is not based on HUNT's Algorithm in constructing the decision tree, rather it partitions the training data set recursively using breadth-first greedy technique until each partition belongs to the same leaf node or class. It can be implemented in both
serial and parallel pattern for good data placement and load balancing.
Unlike SLIQ, SPRINT uses two data structures; attribute list and histogram which is not memory resident, this implementation makes SPRINT more suitable for large data sets, thus it removes all the data memory restrictions on data. It handles both continuous and categorical attributes
SPRINT algorithm is a classical algorithm for building a decision tree that is a widely used method of data classification. However, the SPRINT algorithm has high computational cost in the calculation of attribute segmentation.
It stands for Supervised Learning In Ques. It was introduced by Mehta et al (1996). It is a fast scalable decision tree algorithm that can be implemented in serial and parallel pattern. It is not based on HUNT'S Algorithm for decision tree classification. It partitions a training data set recursively using the breadth-first greedy strategy that is integrated with the pre-sorting technique during the tree building phase. In building a decision tree model SLIQ handles both numeric and categorical attributes
One of the main drawbacks of SLIQ is that it uses a class list data structure that is memory resident, thereby imposing memory restrictions on the data. It uses Minimum Description Length Principle(MDL) in pruning the tree after constructing it MDL is an inexpensive technique in tree pruning that uses the least amount of coding in producing trees that is small in size using the bottom-up technique.
The main advantage of the SLIQ decision tree algorithm is that it produces accurate decision trees that are significantly smaller than the trees produced
using C4.5 and CART. At the same time, SLIQ executes nearly an order of magnitude faster than CART.