# Meta Classification Model of Surface Appearance for Small Dataset Using Parallel Processing

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## Abstract

**:**

## 1. Introduction

## 2. Literature Review

## 3. Research Methodology

#### 3.1. System Overview

#### 3.2. Hypothesis for Images—Low-Level Image Processing

#### 3.3. Evaluation Criteria on Performance Measure Indices

#### 3.4. Tool and Language

## 4. Dataset Preprocessing

#### 4.1. Dataset Overview

#### 4.2. Dataset Processing and Preparation

#### 4.2.1. Missing Values and Outliers Detection

#### 4.2.2. Univariate, Bivariate, and Multivariate Analysis

- The average distance between protrusions and the average number of protrusions are highly correlated (0.85).
- Max height and average height of protrusions are correlated as well (0.96).
- Shade and brightness are highly correlated (0.96).

#### 4.2.3. Categorical Columns (One-Hot Encoding)

#### 4.2.4. Imbalanced Data (Resampling)

#### 4.2.5. Splitting the Dataset

#### 4.2.6. Feature Scaling

## 5. Classification Algorithms

#### 5.1. Decision Tree, Logistic Regression, and Adaboost Classifiers

#### 5.2. Deep Learning Model (Neural Networks) Classifier

#### 5.2.1. Neural Network Architecture

#### 5.2.2. Hyperparameter Optimization Using Parallel Processing with Shared Memory

## 6. Performance Results

## 7. Discussion

## 8. Conclusions and Future Work

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

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Dimension | Value | |||||
---|---|---|---|---|---|---|

Algorithm | Decision Tree | Bagging Classifier (Decision Tree Base) | Logistic Regression | Ada Boost (Logistic Regression Base) | Random Forest | Neural Network |

Confusion Matrix | [52 12] [9 37] | [49 15] [3 43] | [45 19] [6 40] | [45 19] [5 41] | [55 9] [6 40] | [56 5] [3 46] |

Accuracy | 0.809 | 0.836 | 0.772 | 0.782 | 0.863 | 0.927 |

Precision | 0.81 | 0.86 | 0.8 | 0.81 | 0.87 | 0.92 |

Recall | 0.81 | 0.84 | 0.77 | 0.78 | 0.86 | 0.95 |

F1 Score | 0.81 | 0.84 | 0.77 | 0.78 | 0.86 | 0.93 |

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**MDPI and ACS Style**

Kazoom, R.; Birman, R.; Hadar, O.
Meta Classification Model of Surface Appearance for Small Dataset Using Parallel Processing. *Electronics* **2022**, *11*, 3426.
https://doi.org/10.3390/electronics11213426

**AMA Style**

Kazoom R, Birman R, Hadar O.
Meta Classification Model of Surface Appearance for Small Dataset Using Parallel Processing. *Electronics*. 2022; 11(21):3426.
https://doi.org/10.3390/electronics11213426

**Chicago/Turabian Style**

Kazoom, Roie, Raz Birman, and Ofer Hadar.
2022. "Meta Classification Model of Surface Appearance for Small Dataset Using Parallel Processing" *Electronics* 11, no. 21: 3426.
https://doi.org/10.3390/electronics11213426