Causal feature selection with missing data. ACM Transactions on Knowledge Discovery from Data, vol.16, no. 4, Article number 66, 2022. DOI: https://doi.org/10.1145/3488055. X. J. Guo, K. Yu, F. Y. Cao, P. P. Li,
Ciarán M Lee, and Saurabh Johri. 2020. Improving the accuracy of medical diagnosis with causal ...
Causal learning 的一个重要话题是解决out-of-distribtution，要解决它我们可以学习caual feature，causal ...
handling of missing values and masks p-value correction and (bootstrap) confidence interval estimation causal effect class to non-parametrically estimate (conditional) causal effects and also linear mediated causal effects prediction class based on sklearn models including causal feature selection ...
(Publication) Uplift Modeling for Multiple Treatments with Cost Optimization at 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA) (Publication) Feature Selection Methods for Uplift Modeling Citation To cite CausalML in publications, you can refer to the following sources:...
We’re coming out of a hallucinatory period when we thought that the data would be enough. It’s still a concern how few data scientists think about their data collection methods, telemetry, how their analytical decisions (such as removing rows with missing data) introduce statistical bias, and...
Koller D, Sahami M (1996) Toward optimal feature selection. Technical report, Stanford InfoLab Google Scholar Westreich D, Cole SR, Young JG, Palella F, Tien PC, Kingsley L, Gange SJ, Hernán MA (2012) The parametric g-formula to estimate the effect of highly active antiretroviral therapy...
Feature selection: In our case study, the outcome of interest is ‘Delay’, and treatment variables of interest that could be reasonably controlled by the buyers, are the season the order was given in and whether the supplier supplied to multiple warehouses. The latter decision was made due ...
For feature input, the bootstrap samples are generated by selecting a single feature randomly and including it and its eight closest neighboring features in the sample. This random selection repeats with replacement until at least M observations are included in the bootstrap sample. The sa...
However, the discussion has been revived with the development of new computational tools for data analysis. It is now largely uncontroversial that machine learning tools can aid discovery, though there is still debate about whether they generate new knowledge or merely speed up data processing. ...