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Comparison between some of linear classification models with practical application
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Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs two groups when the response variable with tow categorise only.

The first form is the linear discriminant function ,The second is the probability form which it is derivative as alternative for the linear discriminant function while the third form is the probability function model. Of the logistic regression the comparison between these methods is based on measure of the probability  of misclassification .We show that the results of the  probability form  of the logistic regression has minimum probability of misclassification through the application on the data of two types of (leukemia).

 

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Publication Date
Sun Oct 02 2016
Journal Name
Journal Of Educational And Psychological Researches
Personality Types According to Holland's Theory and its Relationship with the Management Changing for some Administrators in the Province of Kurdistan-Iraq
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The figure of personality modes determines its privileged style in the use of modern and advanced technological tools in the process of changing and developing in order to keep up with that. The proses of selection and choosing administrators in the appropriate places are the most important functions of senior management because it is easy to adopt factory buildings or establishments But this is a human world as that of machines world. So it is required to have people in the process of changing those who have a time, Knowledge, skill, ability and strong administrative personal skills, those people (leaders) should to put a clear vision for the selection and application of the change efforts and to create the necessary climate and

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Publication Date
Wed Jun 01 2022
Journal Name
Innovations
Proteolytics, Their Functional Role and Practical Applications
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RMK Al-Zaid, AT Al-Musawi, SJ Mohammad

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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Science
Study the correlation between Human Chorionic Gonadotropin Hormone and Some Biochemical Parameters in Iraqi Women with Pregnancy-Induced Hypertension
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Publication Date
Thu Jun 30 2022
Journal Name
International Journal Of Drug Delivery Technology
Comparison among the Synthesis of Some Azomethine Derivatives by Classical and Non-classical Methods
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Publication Date
Wed Nov 24 2021
Journal Name
International Journal Of Drug Delivery Technology
Comparison among the Synthesis of Some Azomethine Derivatives by Classical and Non-classical Methods
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الوصف In this time, most researchers toward about preparation of compounds according to green chemistry. This research describes the preparation of 2-fluoro-5-(substituted benzylideneamino) benzonitrile under reflux and microwave methods. Six azomethine compounds (B1-6) were synthesized by two methods under reflux and assisted microwave with the comparison between the two methods. Reflux method was prepared of azomethine (B1-6) by reaction of 5-amino-2-fluorobenzonitrile with some aldehyde derivatives with (50–100) mL of absolute ethanol and some quantity of GAA and time is limited between (2–5) hours with a yield between (60–70) percent with recrystallization for appropriate solvents. But the microwave-assisted method was synthe

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Publication Date
Thu Apr 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Proposed Wavelet and Forecasting Wind Speed with Application
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Time series analysis is the statistical approach used to analyze a series of data. Time series is the most popular statistical method for forecasting, which is widely used in several statistical and economic applications. The wavelet transform is a powerful mathematical technique that converts an analyzed signal into a time-frequency representation. The wavelet transform method provides signal information in both the time domain and frequency domain. The aims of this study are to propose a wavelet function by derivation of a quotient from two different Fibonacci coefficient polynomials, as well as a comparison between ARIMA and wavelet-ARIMA. The time series data for daily wind speed is used for this study. From the obtained results, the

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Comparing the Sequential Nonlinear least squared Method and Sequential robust M method to estimate the parameters of Two Dimensional sinusoidal signal model:
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Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust  M method after their development through the use of sequential  approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Some K-Banhatti Polynomials of First Dominating David Derived Networks
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Chemical compounds, characteristics, and molecular structures are inevitably connected. Topological indices are numerical values connected with chemical molecular graphs that contribute to understanding a chemical compounds physical qualities, chemical reactivity, and biological activity. In this study, we have obtained some topological properties of the first dominating David derived (DDD) networks and computed several K-Banhatti polynomials of the first type of DDD.

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