DrivenData Labs

MAY 24, 2023

Several additional approaches were attempted but deprioritized or entirely eliminated from the final workflow due to lack of positive impact on the validation MAE. As an aspiring researcher, Suraj is committed to exploring the potential of AI-driven solutions to revolutionize the healthcare industry.

Machine Learning 225

Machine Learning Machine Learning Data Science Decision Trees 225

Pickl AI

MARCH 5, 2025

So, accuracy is: Case Study: Predicting the Iris Dataset with a Decision Tree The Iris dataset contains flower measurements that classify flowers into three types: Setosa, Versicolor, and Virginica. A Decision Tree model analyses these measurements and makes predictions. The total number of cases is 100.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Cross Validation 52

DrivenData Labs

MAY 22, 2024

Also, I have 10 years of experience with C++ cross-platform development, especially in the medical imaging domain, and for embedded solutions. Vitaly Bondar: ML Team lead in theMind (formerly Neuromation) company with 6 years of experience in ML/AI and almost 20 years of experience in the industry.

Cross Validation 130

Cross Validation Machine Learning Machine Learning ML 130

Ocean Protocol

NOVEMBER 28, 2024

2nd Place: Yuichiro “Firepig” [Japan] Firepig created a three-step model that used decision trees, linear regression, and random forests to predict tire strategies, laps per stint, and average lap times. Firepig refined predictions using detailed feature engineering and cross-validation.

Cross Validation 85

Cross Validation Decision Trees Data Scientist Data Science 85

Pickl AI

JULY 12, 2024

Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development. Python is renowned for its simplicity and versatility, making it an ideal choice for AI applications.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

JULY 26, 2023

Here are some examples of variance in machine learning: Overfitting in Decision Trees Decision trees can exhibit high variance if they are allowed to grow too deep, capturing noise and outliers in the training data. Regular cross-validation and model evaluation are essential to maintain this equilibrium.

Machine Learning 52

Machine Learning Machine Learning Cross Validation Decision Trees 52

Pickl AI

DECEMBER 10, 2024

They vary significantly between model types, such as neural networks , decision trees, and support vector machines. Decision Trees Hyperparameters such as the maximum depth of the tree and the minimum samples required to split a node control the complexity of the tree and help prevent overfitting.

Machine Learning 52

Machine Learning Machine Learning Cross Validation Decision Trees 52

Pickl AI

JANUARY 8, 2025

Tree-Based Methods Decision trees and ensemble methods like Random Forest and Gradient Boosting inherently perform feature selection. Here, we discuss two critical aspects: the impact on model accuracy and the use of cross-validation for comparison.

Machine Learning 52

Machine Learning Machine Learning Cross Validation Support Vector Machines 52

Mlearning.ai

FEBRUARY 10, 2024

However, what drove the development of Bayes’ Theorem, and how does it differ from traditional decision-making methods such as decision trees? Traditional models, such as decision trees, often rely on a deterministic approach where decisions branch out based on known conditions. 466 accuracy 0.77

Algorithm 52

Algorithm Decision Trees Cross Validation Machine Learning 52

Pickl AI

NOVEMBER 18, 2024

Basics of Machine Learning Machine Learning is a subset of Artificial Intelligence (AI) that allows systems to learn from data, improve from experience, and make predictions or decisions without being explicitly programmed. Decision trees are easy to interpret but prone to overfitting. For a regression problem (e.g.,

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

MAY 17, 2023

K-fold Cross Validation ML experts use cross-validation to resolve the issue. As a part of this course, you will learn in-depth about the concepts of Data science, Machine Learning and AI. To test this, you decide to create a validation set, with another 1000 data points.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

FEBRUARY 12, 2024

Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. What is cross-validation, and why is it used in Machine Learning?

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 19, 2025

Despite computational costs, Boosting remains vital for handling complex data and optimising AI models for high-performance decision-making. It works by training multiple weak models (often decision trees with one split, known as stumps). Introduction Boosting in Machine Learning is a powerful ensemble technique.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 52

Pickl AI

JANUARY 3, 2024

EDA, imputation, encoding, scaling, extraction, outlier handling, and cross-validation ensure robust models. Feature importance from trees Objective: Leveraging decision tree-based models to assess feature importance.

Machine Learning 52

Machine Learning Machine Learning Exploratory Data Analysis Cross Validation 52

Pickl AI

SEPTEMBER 12, 2024

Artificial Intelligence (AI): A branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. Cross-Validation: A model evaluation technique that assesses how well a model will generalise to an independent dataset.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

DECEMBER 12, 2024

Introduction Boosting is a powerful Machine Learning ensemble technique that combines multiple weak learners, typically decision trees, to form a strong predictive model. Lets explore the mathematical foundation, unique enhancements, and tree-pruning strategies that make XGBoost a standout algorithm. Lower values (e.g.,

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

OCTOBER 15, 2024

Techniques like linear regression, time series analysis, and decision trees are examples of predictive models. At each node in the tree, the data is split based on the value of an input variable, and the process is repeated recursively until a decision is made.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 52

Pickl AI

NOVEMBER 28, 2024

Decision Trees These trees split data into branches based on feature values, providing clear decision rules. These platforms provide Machine Learning-specific tools such as Amazon SageMaker, Google AI Platform, and Azure Machine Learning that simplify model development, training, and deployment.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Mlearning.ai

NOVEMBER 29, 2023

Decision Trees ML-based decision trees are used to classify items (products) in the database. In its core, lie gradient-boosted decision trees. For instance, when used with decision trees, it learns to outline the hardest-to-classify data instances over time. But the results should be worth it.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

MAY 24, 2023

Its modified feature includes the cross-validation that allowing it to use more than one metric. LightGBM Gradient Boosting is a significant machine learning toolbox which helps developers in developing innovative algorithms by utilising defined fundamental models, specifically decision trees.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 4, 2024

From linear regression to decision trees, Alteryx provides robust statistical models for forecasting trends and making informed decisions. Alteryx’s validation tools, such as the Cross-Validation Tool, ensure the accuracy and reliability of predictive models.

Data Preparation 52

Data Preparation Tableau Data Visualization Analytics 52

Pickl AI

AUGUST 9, 2024

Key topics include: Supervised Learning Understanding algorithms such as linear regression, decision trees, and support vector machines, and their applications in Big Data. Model Evaluation Techniques for evaluating machine learning models, including cross-validation, confusion matrix, and performance metrics.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

NOVEMBER 2, 2023

linear regression, decision trees , SVM) – Understanding about the perfect fit for using each algorithm – Parameters and hyperparameters to tune Click here to access -> Cheat sheet for Key Machine Learning Algorithms Deep Learning Concepts and Neural Network Architectures – Neural network components and their functions (e.g.,

Data Scientist 52

Data Scientist Data Science Data Visualization Machine Learning 52

Pickl AI

APRIL 26, 2024

Techniques such as cross-validation, regularisation , and feature selection can prevent overfitting. What are the advantages and disadvantages of decision trees ? Overfitting occurs when a model learns the training data too well, including noise and irrelevant patterns, leading to poor performance on unseen data.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

DagsHub

APRIL 21, 2024

Especially in the current time when LLM models are making their way for several industry-based generative AI projects. PyTorch Developed by Facebook’s AI Research Lab (FAIR), PyTorch is a popular machine-learning framework that offers a flexible and dynamic approach to building and training neural networks.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Mlearning.ai

JANUARY 29, 2024

Data Science Project — Build a Decision Tree Model with Healthcare Data Using Decision Trees to Categorize Adverse Drug Reactions from Mild to Severe Photo by Maksim Goncharenok Decision trees are a powerful and popular machine learning technique for classification tasks.

Decision Trees 52

Decision Trees Data Science Exploratory Data Analysis Data Analysis 52

DrivenData Labs

MAY 1, 2025

I studied Computer Science and really enjoyed the AI space, although hardware resources were always limited, which shaped my push to always simplify. Summary of approach: I used LightGBM decision tree algorithm to predict the difference between test participants scores from different years.

Decision Trees 147

Decision Trees Clustering Algorithm Machine Learning 147

DagsHub

JUNE 3, 2024

Image Credits: The New York Times Read more: [link] In another 2018 story , Amazon was found to show bias toward male candidates in the recruitment process because of an issue with their AI-powered HR recruiting tool. In such cases, you’d benefit more from a decision tree or a linear model.

Machine Learning 52

Machine Learning Machine Learning Decision Trees ML 52

Mlearning.ai

JULY 14, 2023

Random forests inherit the benefits of a decision tree model whilst improving upon the performance by reducing the variance. —  Jeremy Jordan Random Forest is a popular and powerful ensemble learning algorithm that combines multiple decision trees to generate accurate and stable predictions.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Cross Validation 52

Towards AI

JULY 19, 2023

Last Updated on July 19, 2023 by Editorial Team Author(s): Anirudh Chandra Originally published on Towards AI. In our exercise, we will try to deal with this imbalance by — Using a stratified k-fold cross-validation technique to make sure our model’s aggregate metrics are not too optimistic (meaning: too good to be true!)

Machine Learning 40

Machine Learning Machine Learning K-nearest Neighbors Support Vector Machines 40

Dataconomy

SEPTEMBER 1, 2023

The time has come for us to treat ML and AI algorithms as more than simple trends. We are no longer far from the concepts of AI and ML, and these products are preparing to become the hidden power behind medical prediction and diagnostics. The decision tree algorithm used to select features is called the C4.5

Decision Trees 195

Decision Trees Machine Learning Machine Learning Support Vector Machines 195