Literature Review
In this particular chapter, all the required background information concerning the main idea of the thesis has been given. The thesis also discusses the SVM learning technique which is needed for producing a classification model. This particular model also highlights about SVM classifier — the information focuses on the idea of machine learning techniques which has helped the officer in solving this case. It will ultimately help in solving various kinds of issues or cases. The background information helps in having an idea regarding graphical interface that provides an easy way for securing both data and enabling the use of police based services. There are various kinds of predictive modelling techniques which are available in the present scenario. It is considered to be free from commercially-based software. The subsequent section of the report mainly deals with implementation of predictive modelling technique which has been discussed in details.
Machine learning depends on the ability of various systems to learn and implement new techniques of human interface efficiently. Machine algorithm is mainly used for the purpose of prediction and description. Machine learning algorithm is used for explaining in a better way with the help of linear classifier in the machine world. A proper idea has been provided concerning the application of machine learning classification. It is mainly used for understanding the various kinds of risks related to diseases which are encountered in MRI structure. Its application helps in analysing machine learning based algorithm by making use of the MRI approach. The MRI structure of brain highlights that there is no direct way which is needed for finding data from clinical practice. It has been implemented so that machine learning based application can be easily used for the diagnosis of MRI data. In this particular application, both kind of SVM and Naïve Bayes can be easily used for classification of MRI data. In this specific application, both the methods of SVM and Naïve Bayes can be easily used for responding and prediction of treatment. In some of the general cases, MRI brain application makes use of SVM, which provides a value between the given value of 67.6 and 90.3. MRI brain application is used for calculating the overall accuracy for predicting treatment response. This particular study highlights specific sets of genes which are considered to be similar to the method of expression data. It mainly highlights various kinds of SVM model along with a different variety of metrics. SVM model has been implemented so it can easily classify the given genes by making use of the proper expression. The dataset which is used in this expression comes up with genes of records that have 79 different DNA microarrays.Kernel-based functions in the SVM model which comes up with the best prediction for unannotated along with identifying the role of yeast genes. The ultimate focus is on the fact that SVM methods and predictive analytics can be used for improving the decision for protecting youth. The kernel function of the SVM model focuses on providing the best kind of prediction which is needed for identifying the overall purpose of genes. The result highlighted the fact that SVM models so that they can perform four other types of methods. In this case, two specific kinds of decision tree have been provided.
Background Information
SVM is known to be a statistical method which is needed for learning algorithm in various zones. SVM method has been applied to multiple zones of audio classification along with retrieval of research. Depending on the study, the issue of audio classification can be built by SVM along with a strategy for recognising binary tree. For this particular research, the method of audio retrieval has been given along with a new kind of metric. In the instances of binary tree recognition, the system focus on gathering inside audio data. The system aims to calculate DFB (Distance from the boundary) which is needed for calculatingboth audio data and SVM.
The ultimate output of this research focuses on the fact that audio classification which can be effectively used from SVM along with achieving a value of low rate. The total computation of DFB is all about having a large number of vectors.
SVM classifiers come up with various kind of examination of remote sensing of images. In this particular experiment, proper optimization of the framework is needed for analyzing and along with an estimation of SVM classification perimeters. The ultimate goal of SVM classifier is all about examining the overall accuracy. It highlights the fact that system needs detection of a proper kind of subset, which is required for discrimination and overcoming of the selected issues in SVM classifier. It is mainly done so that a generic algorithm, like GA is appropriately used. In this experiment, there are mostly two kinds of classifiers; SVM-GA-SV and SVM-GA-R2W2, which are needed for controlling environment. SVM-GA-SV is compared with SVM-GA-R2W2 so that probability of discriminative feature among the noisy one and leading accuracy has been discussed in details. In the experiment, SVM-GA-SV classifier aims to provide much better capability for detecting noise. It ultimately leads to much upper kind of classification based accuracy in comparison to SVM-GA-R2W2 classifier. SVM-GA-SV comes up with 43 features by making use of SVM classifier. It is mainly applied so that it can work directly with the available hyper-dimensional space. SVM classifier aims to provide required training data into requiring subsets and models along with two classifiers. The overall value of SVM-GA-SV is considered to be around $87.66. SVM-GA-R2W2 focuses on detecting 133 features by making use of SVM classifier. It focuses on understanding the accuracy changes in comparison to another kind of classifier. The overall result of SVM-GA-R2W2 experiment is found to be around 91.05. In the coming chapters, the linear classifier model has been explained along with implementing of missing youth database.
For this particular reason, a missing individual can be easily referred to as reported the issue of missing for the interval of a few hours to months in the given policy agency. In 2005, a various employees of Saskatchewan police policies understood the importance of MY database. Depending on the report of MY files, there is a large number of records which needs to be taken into consideration. The dataset comes up with records of 2956 records for each of the MY cases. It mainly highlights the fact that individual can easily report for more than one case in the matters of issues for runaways. Data is this particular age can be used for proper kind of distribution along with significant numbers for missing cases for which the amount varies from 9 to 18. The ultimate result of this particular report is all about analysis for youth runaways.
SVM Learning Technique
Various agencies have performed two kinds of action which are needed for reducing the overall number of runaways. The primary focus is all about shifting the monthly discussion and helping the youth in dealing with problem risk of youth. The next step is all about providing ongoing and technical support and services. As per the Partnership Committee of Saskatchewan, youth come up with a risk of MP in Saskatchewan. The main task is related to various kind of individual for understanding risk. It is needed for understanding the overall roles and responsibilities. MP committee of Saskatchewan comes up with a health program, community council and publication, which is necessary for creating awareness. The health education program focuses on on-going education that aims to provide information along with risk associated with cases of the missing youth.
As per the topic of the researcher, an idea has been provided concerning predictive analysis which can quickly help in improving the possible decision-making protection of youth. In 2008, the research focuses on creating classification and regression tree analysis (CART). CPS system aims to provide the best kind of services which is needed for families and child. The output of this study is all about neglecting and multiplying.
Recent research has highlighted one of the significant points which are needed by the police department. It is mainly required for understanding the data provided in the police investigation. The police department has come across the fact that they need a reasonable and absolute number of initiatives for dealing with violence. The police department can easily make use of software program and analytical tool for solving various kinds of issues. A software application mainly runs with the help of GUI (Graphical User Interface). GUI has been intended to that it can provide a certain number of visual indications towards better kind of decision making. It aims to focus decision making and analytical tool which is needed for overcoming a large number of issues. GUI can be used in the police department so that it can be easily used for collecting information with the help of graphical icons and visual based indicators. GUI can be easily used for tracking a different kind of processes like crimes, their types and criminal history. It can quickly provide examples of a software program which is needed by police for solving the given task.
Proper development of technologies related to information and communication can help in getting faster method of generating and data sharing. There isa large number of security organization which can provide preventive measures for software programs. It is mainly needed for dealing with future crimes and crime based records which are required for collecting and analysing data with the help of crime investigation. There is a large number of data mining techniques like machine learning, intelligent agents which are needed for classifying and predicting design. The research has been done so that an idea can be collected with respect to criminalsand proper informationbe extracted fromhidden network structure that is built among the employees. It is mainly done so that criminal investigation and forensic science can be offered by various machine learning algorithms. The algorithms are implemented in the database at a much faster rate without data analysis knowledge recruitment by GUI. In this thesis paper, the overall method of MP GUI can be easily implemented which aims to provide analysis and reporting by the help of SPS.
References
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Pfeifer, J. (2006), Missing persons in Saskatchewan: Police policy and practice, Law Foundation of Saskatchewan Chair in Police Studies, University of Regina Department of Forensic and Social Psychology.
(2015), Saskatoon Police Service 2015-2019 Business Plan, Saskatoon Police Service (SPS), available at https://saskatoonpolice.ca/pdf/general/Business_Plan_2015-19.pdf.
(2007), Final Report of the Provincial Partnership Committee on Missing Persons, Saskatchewan Towards Offering Partnership Solutions To Violence Inc. (STOPS to Violence), available at https://publications.gov.sk.ca/documents/9/30559-missing-persons-final.pdf.
Bonny, E., L. Almond, and P. Woolnough (2016), Adult missing persons: Can an investigative framework be generated using behavioural themes?, Journal of Investigative Psychology and Offender Profiling, 13 (3),296–312.
Russell, J., and S. Macgill (2015), Demographics, policy, and foster care rates; a predictive analytics approach, Children and Youth Services Review, 58, 118–126.
Sledjeski, E. M., L. C. Dierker, R. Brigham, and E. Breslin (2008), The use of risk assessment to predict recurrent maltreatment: A classification and regression tree analysis (cart), Prevention science, 9 (1), 28–37.
Brookes, D., and D. Webster (1999), Child welfare in the united states: Policy, practice and innovations in service delivery, International Journal of Social Welfare, 8 (4), 297–307.
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