핵톤의 사용자 기여

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2024년 11월 4일 (월)

  • 11:472024년 11월 4일 (월) 11:47 차이 역사 −4‎ Entropy (Data Science) ‎편집 요약 없음 태그: 시각 편집
  • 11:462024년 11월 4일 (월) 11:46 차이 역사 +2,577‎ 새글 Entropy (Data Science) ‎ Created page with "'''Entropy (Data Science)''' In '''Data Science''', '''Entropy''' is a measure of randomness or uncertainty in a dataset. Often used in Decision Trees and other machine learning algorithms, entropy quantifies the impurity or unpredictability of information in a set of data. In classification tasks, entropy helps determine the best way to split data to reduce uncertainty and increase homogeneity in the resulting subsets. ==How Entropy Works== Entropy, denoted as H, is ca..." 태그: 시각 편집
  • 11:432024년 11월 4일 (월) 11:43 차이 역사 +3,463‎ 새글 Decision Tree ‎ Created page with "'''Decision Tree''' A '''Decision Tree''' is a supervised learning algorithm used for both classification and regression tasks. It structures decisions as a tree-like model, where each internal node represents a test on a feature, each branch represents an outcome of that test, and each leaf node represents a class label or prediction. Decision Trees are highly interpretable and can work with both categorical and numerical data, making them widely applicable across vari..." 최신 태그: 시각 편집
  • 11:392024년 11월 4일 (월) 11:39 차이 역사 +3,898‎ 새글 Random Forest ‎ Created page with "'''Random Forest''' is an ensemble learning method that combines multiple Decision Trees to improve classification or regression accuracy. It is designed to mitigate the limitations of single Decision Trees, such as overfitting and sensitivity to data variations, by building a "forest" of trees and aggregating their predictions. This approach often leads to greater model stability and accuracy. ==How It Works== Random Forest creates multiple Decision Trees during trainin..." 최신 태그: 시각 편집
  • 11:342024년 11월 4일 (월) 11:34 차이 역사 +34‎ Support Vector Machine ‎편집 요약 없음 최신 태그: 시각 편집
  • 11:332024년 11월 4일 (월) 11:33 차이 역사 +26‎ Logistic Regression ‎편집 요약 없음 최신 태그: 시각 편집
  • 11:332024년 11월 4일 (월) 11:33 차이 역사 +3,885‎ 새글 Logistic Regression ‎ Created page with "'''Logistic regression''' is a statistical and machine learning algorithm used for binary classification tasks, where the output variable is categorical and typically represents two classes (e.g., yes/no, spam/not spam, fraud/not fraud). Despite its name, Logistic Regression is a classification algorithm, not a regression algorithm, as it predicts probabilities of classes rather than continuous values. ==How It Works== Logistic Regression models the probability of a bin..." 태그: 시각 편집
  • 11:332024년 11월 4일 (월) 11:33 차이 역사 −3,900‎ Logistic regression ‎ Redirected page to Logistic Regression 최신 태그: 새 넘겨주기 시각 편집
  • 11:292024년 11월 4일 (월) 11:29 차이 역사 +4,198‎ 새글 Support Vector Machine ‎ Created page with "'''Support Vector Machine (SVM)''' is a powerful supervised machine learning algorithm used for both classification and regression tasks, though it is primarily used in classification. SVM works by finding the optimal boundary, or hyperplane, that best separates the data points of different classes. SVM is effective in high-dimensional spaces and is especially suitable for binary classification problems. ==How It Works== SVM aims to maximize the margin between data point..." 태그: 시각 편집
  • 11:242024년 11월 4일 (월) 11:24 차이 역사 +10‎ Logistic regression ‎편집 요약 없음 태그: 시각 편집
  • 11:222024년 11월 4일 (월) 11:22 차이 역사 +2,216‎ Logistic regression ‎편집 요약 없음 태그: 시각 편집: 전환됨
  • 11:202024년 11월 4일 (월) 11:20 차이 역사 +49‎ Regression Algorithm ‎편집 요약 없음 최신 태그: 시각 편집
  • 11:182024년 11월 4일 (월) 11:18 차이 역사 +42‎ Independence (Linear Regression) ‎편집 요약 없음 최신 태그: 시각 편집
  • 11:182024년 11월 4일 (월) 11:18 차이 역사 +2,379‎ 새글 Independence (Linear Regression) ‎ Created page with "In the context of '''Linear Regression''', '''independence''' refers to the assumption that each observation in the dataset is independent of the others. This assumption is crucial for producing unbiased estimates and valid predictions. When observations are independent, it implies that the value of one observation does not influence or provide information about another observation. ==Importance of the Independence Assumption== Independence is a foundational assumption f..." 태그: 시각 편집
  • 11:152024년 11월 4일 (월) 11:15 차이 역사 +3,427‎ 새글 Linear Regression ‎ Created page with "'''Linear Regression''' is a fundamental regression algorithm used in machine learning and statistics to model the relationship between a dependent variable and one or more independent variables. It assumes a linear relationship between the variables, which means the change in the dependent variable is proportional to the change in the independent variables. Linear Regression is commonly used for predictive analysis and trend forecasting. ==Types of Linear Regression== T..." 최신 태그: 시각 편집
  • 11:102024년 11월 4일 (월) 11:10 차이 역사 +3,307‎ 새글 분류:Data Science ‎ Created page with "The field of '''Data Science''' encompasses a wide range of concepts, techniques, and tools focused on extracting insights and knowledge from data. It involves interdisciplinary approaches from statistics, computer science, mathematics, and domain-specific expertise to process, analyze, and interpret complex datasets. Data Science is applied across various industries, including healthcare, finance, marketing, and technology, to make data-driven decisions, predict trends,..." 최신 태그: 시각 편집
  • 11:082024년 11월 4일 (월) 11:08 차이 역사 +2,011‎ 새글 Discrete ‎ Created page with "In mathematics and computer science, '''discrete''' refers to distinct, separate values or entities, as opposed to continuous values. Discrete data or structures consist of isolated points or categories, often represented by integers or categorical labels. In contrast, continuous data have values that fall within a range and can take on any value within that interval. ==Examples of Discrete Data== Discrete data is commonly found in many fields and applications: *'''Count..." 최신 태그: 시각 편집
  • 11:062024년 11월 4일 (월) 11:06 차이 역사 +26‎ Classification Algorithm ‎편집 요약 없음 최신 태그: 시각 편집
  • 11:052024년 11월 4일 (월) 11:05 차이 역사 +4,552‎ 새글 Classification Algorithm ‎ Created page with "'''Classification algorithms''' are a group of machine learning methods used to categorize data into discrete classes or labels. These algorithms learn from labeled data during training and make predictions by assigning an input to one of several possible categories. Classification is widely applied in areas like image recognition, spam filtering, and medical diagnosis. ==Types of Classification Algorithms== There are various types of classification algorithms, each with..." 태그: 시각 편집
  • 11:002024년 11월 4일 (월) 11:00 차이 역사 +4,260‎ 새글 Regression Algorithm ‎ Created page with "'''Regression algorithms''' are a family of machine learning methods used for predicting continuous numerical values based on input features. Unlike classification, which predicts discrete classes, regression predicts outputs that can take any real number value. Regression algorithms are widely used in various fields, such as finance, economics, and environmental science, where predicting quantities (like stock prices, sales, or temperatures) is essential. ==Types of Reg..." 태그: 시각 편집
  • 10:572024년 11월 4일 (월) 10:57 차이 역사 +3,441‎ 새글 K-Nearest Neighbor ‎ Created page with "'''K-Nearest Neighbo'''r, often abbreviated as '''K-NN''', is a simple and intuitive classification and regression algorithm used in supervised machine learning. It classifies new data points based on the majority class among its nearest neighbors in the feature space. K-NN is a non-parametric algorithm, meaning it makes no assumptions about the underlying data distribution, making it v..." 최신 태그: 시각 편집
  • 10:462024년 11월 4일 (월) 10:46 차이 역사 +26‎ Data Science ‎편집 요약 없음 최신 태그: 시각 편집
  • 10:462024년 11월 4일 (월) 10:46 차이 역사 +3,635‎ 새글 Data Science ‎ Created page with "Data Science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from both structured and unstructured data. It combines elements of statistics, computer science, and domain expertise to analyze complex data and derive actionable conclusions. The goal of Data Science is often to make data-driven decisions, predict trends, and provide meaningful insights that can guide business and research. ==Key Component..." 태그: 시각 편집
  • 10:442024년 11월 4일 (월) 10:44 차이 역사 +1,003‎ 새글 Bayes' Theorem ‎ Created page with "'''Bayes' theorem''' is a fundamental principle in probability theory and statistics, which describes how to update the probability of a hypothesis based on new evidence. It provides a mathematical framework for reasoning under uncertainty and is often used in machine learning, especially in algorithms like Naive Bayes. The theorem is expressed as: P(A | B) = (P(B | A) * P(A)) / P(B) where: *'''P(A | B)''' is the posterior probability: the probability of event A occur..." 최신 태그: 시각 편집
  • 10:402024년 11월 4일 (월) 10:40 차이 역사 +28‎ Naive Bayes ‎편집 요약 없음 최신 태그: 시각 편집: 전환됨
  • 10:382024년 11월 4일 (월) 10:38 차이 역사 +2,137‎ 새글 Naive Bayes ‎ Created page with "**Naive Bayes** The '''Naive Bayes''' algorithm is a probability-based classification method that calculates the likelihood of data belonging to a specific class by using conditional probabilities. As suggested by the term "naive," this algorithm assumes that each feature is independent of the others. While this assumption is often unrealistic, Naive Bayes proves to be practical and efficient in classification tasks, providing good performance on real-world data. Naive..."

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