• Computer Science
  • Published 2019

Drug activity prediction of small drug molecules using Random Forest model

@inproceedings{Yadav2019DrugAP,
  title={Drug activity prediction of small drug molecules using Random Forest model},
  author={Vineet Yadav and Ujjawal Goel and Tanuj Kumar and Utkarsh lakhera},
  year={2019}
}
The aim of this paper is to develop predictive models that can determine, whether a particular compound is active (1) or not (0). In this, we have different datasets along with the drugs. A dataset contains a number of features. Every feature will be processed by using feature selection algorithms and particular compound also be found with the help of these features. We have taken the dataset from Tox21 databases, clean the data and then apply the different feature selection algorithms in order… CONTINUE READING

Figures, Tables, and Topics from this paper.

Explore Further: Topics Discussed in This Paper

References

Publications referenced by this paper.
SHOWING 1-4 OF 4 REFERENCES

Random Forests

  • Machine Learning
  • 2001
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

mlbench: Machine Learning Benchmark Problems. R package version 2.0-0

F Leisch, E Dimitriadou
  • 2010