Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in categorical outcomes, with the overarching goal of supervised learning being to enhance models capable of predicting class labels based on input features. This review endeavors to furnish a concise, yet insightful reference manual on machine learning, intertwined with the tapestry of statistical learning theory (SLT), elucidating their symbiotic relationship. It demystifies the foundational concepts of classification, shedding light on the overarching principles that govern it. This panoramic view aims to offer a holistic perspective on classification, serving as a valuable resource for researchers, practitioners, and enthusiasts entering the domains of machine learning, artificial intelligence and statistics, by introducing concepts, methods and differences that lead to enhancing their understanding of classification methods.
Background: To evaluate the effect of antierosive agents (10% Nano-Hydroxyapatite (NHA), 10% Casein Phophopeptide-Amorphous Calcium Phosphate (CPP-ACP), and combination of 10% NHA and 10% CPP-ACP) on loss of minerals from enamel surface of permanent teeth treated with antierosive agents when exposed to an acidic beverage and investigate the morphological changes of treated enamel surface after demineralization with cola based beverage under Scanning Electron Microscope (SEM). Materials and Methods: Sixty maxillary first premolars were randomly divided into four groups, 15 teeth for each group. Group I treated with 10% NHA, Group II treated with 10% CPP-ACP, Group III treated with 10% NHA and 10% CPP-ACP, and Group IV did not treat with any
... Show MoreThe study of triples seeks to deal with the comprehensive nature of the Qur’an texts, and the choice fell on the trilogy of great torment, pain, and humiliation in the Noble Qur’an - an objective study, the title of this research, in which I tried to shed light on these terms, and the nuances between them, and in particular torment The eschatological terminology varied, which can be summed up in three terms, namely the great, the painful, and the offensive. The types of torment, the pain is the painful one that is described by the severity of pain and its horror, as for the humiliating punishment, it is that which humiliates the one who has fallen on it, and the diversity of torment is due to the diversity of sins.
Various Hall Effects have been successfully observed in samples of n-type indium antimonide with values for conductivity, energy gap, Hall mobility and Hall coefficient all agreeing with theory. A particular interest in developing a method for obtaining accurate values of carrier concentrations in semiconductor samples has been fulfilled with an experimental result of (1.6×1016 cm-3 ±10.7%) giving a percentage difference of (6.7%) to a quoted value of (1.5×1016cm-3) at (77K) using an (80mW C.W. CO2) laser beam at (10.6μm) to illuminate a similar sample of n-type indium antimonide, an "Optical" Hall effect has been observed. Although some doubt has been raised as to the validity of effect i.e. "thermal" rather than "Optical", values o
... Show MoreFrictional resistance occurs whenever sliding happens, negatively impacting treatment outcomes and duration. It is a clinical challenge and must be dealt with efficiently to achieve the best orthodontic results. Aims of this study: compare and evaluate the static frictional forces under the wet condition to mimic the oral environment produced by using a polycrystalline ceramic bracket, monocrystalline ceramic bracket, 0.014 of an inch nickel-titanium (Rhodium coated archwires, and ilusio aesthetic archwires), and 0.019 x 0.025 of an inch stainless steel (Rhodium coated archwires, and ilusio aesthetic archwires). Ninety-six aesthetic brackets (48 monocrystalline and 48 polycrystalline brackets) were used and stored in different incub
... Show MoreNA Nasir, H Amir, Faculty of medicine - Iraq, 2017 - Cited by 13
Background: Enterococcus faecalis is emerging as an important endodontic pathogen, which can persist in the environment for extended periods after treatment and may cause endodontic failure. It is known to produce biofilms, a community of bacteria enclosed within a protective polymeric matrix. This study aimed to establish whether the biofilm formation by Enterococcus faecalis can be inhibited with steralium, co+steralium, and 5% sodium hypochlorite in the root surface environment. Materials and Methods: Extracted human teeth were biomechanically prepared, vertically sectioned, placed in the tissue culture wells exposing the root canal surface to E. faecalis to form a biofilm. At the end of the 3rd and 6th weeks, all groups were treated fo
... Show MoreDue to restrictions and limitations on agricultural water worldwide, one of the most effective ways to conserve water in this sector is to reduce the water losses and improve irrigation uniformity. Nowadays, the low-pressure sprinkler has been widely used to replace the high-pressure impact sprinklers in lateral move sprinkler irrigation systems due to its low operating cost and high efficiency. However, the hazard of surface runoff represents the biggest obstacle for low-pressure sprinkler systems. Most researchers have used the pulsing technique to apply variable-rate irrigation to match the crop water needs within a normal application rate that does not produce runoff. This research introduces a variable pulsed irrigation algorit
... Show MoreSupport vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
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