A dedicated, Self motivated and persistent individual. Honesty and timeliness are my key tools. A Data scientist currently working on the application of Data mining techniques to solve complex life,health,business, and decision makinig problems. Grinded in Java programming and web application development. Address: Lanzhou University of Technology, Lanzhou, Gansu Province, 1730050
International Journal of Science and Research, 2019
Application of machine learning algorithms for the diagnosis of diabetes have become a trending r... more Application of machine learning algorithms for the diagnosis of diabetes have become a trending research area, as effort to improve current techniques and methods used byhealth care institutions to determine the occurrence of diabetes in individuals is now given more attention than before. This study attempts to evaluate the performance of five (5) machine learning models on diabetic dataset using Python to predict the incidence of diabetes. Pima Indian diabetes dataset from UCI machine learning repository was used for the study. To ensure quality evaluation of the algorithms, a second dataset provided by Dr. John Schorling of the department of Medicine, University of Virginia was used for double evaluation. Result shows that Naive Bayes algorithm performs better when used for the prediction of diabetes.
Diabetes causes a large number of deaths each year and a large number of people living with the d... more Diabetes causes a large number of deaths each year and a large number of people living with the disease do not realize their health condition early enough. In this study, we propose a data mining based model for early diagnosis and prediction of diabetes using the Pima Indians Diabetes dataset. Although K-means is simple and can be used for a wide variety of data types, it is quite sensitive to initial positions of cluster centers which determine the final cluster result, which either provides a sufficient and efficiently clustered dataset for the logistic regression model, or gives a lesser amount of data as a result of incorrect clustering of the original dataset, thereby limiting the performance of the logistic regression model. Our main goal was to determine ways of improving the k-means clustering and logistic regression accuracy result. Our model comprises of PCA (principal component analysis), k-means and logistic regression algorithm. Experimental results show that PCA enhanced the k-means clustering algorithm and logistic regression classifier accuracy versus the result of other published studies, with a k-means output of 25 more correctly classified data, and a logistic regression accuracy of 1.98% higher. As such, the model is shown to be useful for automatically predicting diabetes using patient electronic health records data. A further experiment with a new dataset showed the applicability of our model for the predication of diabetes.
This work is under review for publication. Contact xtianidemudia@yahoo.co.uk for the interim publ... more This work is under review for publication. Contact xtianidemudia@yahoo.co.uk for the interim public report.
Technology is on the rise every now and then. Various aspect of human activities and computationa... more Technology is on the rise every now and then. Various aspect of human activities and computational jobs are been automated with technological advance to either simplify the process or make it more advanced in its relevance. This seminar work is centered on the concept of Night Vision technology and its application.
Traffic congestion has become a major concern for many cities throughout the world. Simulations p... more Traffic congestion has become a major concern for many cities throughout the world. Simulations provide useful tools for engineer to plan traffic systems and government to make decisions. This seminar work will study some existing simulation models which will afford the opportunity to evaluate traffic control and design strategies without committing expensive, time-consuming resources necessary to implement the alternative strategies in the field.
International Journal of Science and Research, 2019
Application of machine learning algorithms for the diagnosis of diabetes have become a trending r... more Application of machine learning algorithms for the diagnosis of diabetes have become a trending research area, as effort to improve current techniques and methods used byhealth care institutions to determine the occurrence of diabetes in individuals is now given more attention than before. This study attempts to evaluate the performance of five (5) machine learning models on diabetic dataset using Python to predict the incidence of diabetes. Pima Indian diabetes dataset from UCI machine learning repository was used for the study. To ensure quality evaluation of the algorithms, a second dataset provided by Dr. John Schorling of the department of Medicine, University of Virginia was used for double evaluation. Result shows that Naive Bayes algorithm performs better when used for the prediction of diabetes.
Diabetes causes a large number of deaths each year and a large number of people living with the d... more Diabetes causes a large number of deaths each year and a large number of people living with the disease do not realize their health condition early enough. In this study, we propose a data mining based model for early diagnosis and prediction of diabetes using the Pima Indians Diabetes dataset. Although K-means is simple and can be used for a wide variety of data types, it is quite sensitive to initial positions of cluster centers which determine the final cluster result, which either provides a sufficient and efficiently clustered dataset for the logistic regression model, or gives a lesser amount of data as a result of incorrect clustering of the original dataset, thereby limiting the performance of the logistic regression model. Our main goal was to determine ways of improving the k-means clustering and logistic regression accuracy result. Our model comprises of PCA (principal component analysis), k-means and logistic regression algorithm. Experimental results show that PCA enhanced the k-means clustering algorithm and logistic regression classifier accuracy versus the result of other published studies, with a k-means output of 25 more correctly classified data, and a logistic regression accuracy of 1.98% higher. As such, the model is shown to be useful for automatically predicting diabetes using patient electronic health records data. A further experiment with a new dataset showed the applicability of our model for the predication of diabetes.
This work is under review for publication. Contact xtianidemudia@yahoo.co.uk for the interim publ... more This work is under review for publication. Contact xtianidemudia@yahoo.co.uk for the interim public report.
Technology is on the rise every now and then. Various aspect of human activities and computationa... more Technology is on the rise every now and then. Various aspect of human activities and computational jobs are been automated with technological advance to either simplify the process or make it more advanced in its relevance. This seminar work is centered on the concept of Night Vision technology and its application.
Traffic congestion has become a major concern for many cities throughout the world. Simulations p... more Traffic congestion has become a major concern for many cities throughout the world. Simulations provide useful tools for engineer to plan traffic systems and government to make decisions. This seminar work will study some existing simulation models which will afford the opportunity to evaluate traffic control and design strategies without committing expensive, time-consuming resources necessary to implement the alternative strategies in the field.
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Papers by idemudia christian
This seminar work is centered on the concept of Night Vision technology and its application.
This seminar work will study some existing simulation models which will afford the opportunity to evaluate traffic control and design strategies without committing expensive, time-consuming resources necessary to implement the alternative strategies in the field.
This seminar work is centered on the concept of Night Vision technology and its application.
This seminar work will study some existing simulation models which will afford the opportunity to evaluate traffic control and design strategies without committing expensive, time-consuming resources necessary to implement the alternative strategies in the field.