Dimensionality reduction of microarray data is a very challenging task due to high computational time and the large amount of memory required to train and test a model. Genetic programming (GP) is a stochastic approach to solving a problem. For high dimensional datasets, GP does not perform as well as other machine learning algorithms. To explore the inherent property of GP to generalize models from low dimensional data, we need to consider dimensionality reduction approaches. Random projections (RPs) have gained attention for reducing the dimensionality of data with reduced computational cost, compared to other dimensionality reduction approaches. We report that the features constructed from RPs perform extremely well when combined with a GP approach. We used eight datasets out of which seven have not been reported as being used in any machine learning research before. We have also compared our results by using the same full and constructed features for decision trees, random forest, naive Bayes, support vector machines and k-nearest neighbor methods.
Slaughterhouse workers (SHW) are at increased risk of hepatitis which can occur due to different organisms and should be investigated for viral, bacterial, and parasitic organisms. Slaughter house personnel including butchers are at a higher risk of infections from cuts and blood-letting, with the possible risk of the transmission of blood-borne pathogens to their colleagues. The objective of this review is to evaluate the common etiologies of hepatitis in SHW which will assist in the assessment of these patients presenting with transaminitis. Types of Microorganisms causing hepatitis with their reservoirs, routes of transmission, laboratory diagnosis, clinical features, treatment options and preventive strategies are included in this review. Proper investigation and awareness is of utmost importance as it causes significant financial constraints derived from workers health cost and from livestock production losses when the disease is confirmed. The work up is essential because infected workers might be a source of infections to other colleagues, family and the consumers.
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