Regression
Artificial Intelligence
Applying Machine Learning to the Evaluation of Fuel Emissions Dataset Overview Exploratory Data Evaluation Constructing Regression Models Data Preparation Conclusion
Welcome to my blog, where I express my interest for applying machine learning to discover long-term solutions to environmental problems. Today, I’d need to discuss one of the vital pressing problems with our time:...
Artificial Intelligence
Top 10 Machine Learning Algorithms Every Programmer Should Know #1. Linear Regression: The Oldie but Goodie #2. Logistic Regression: It’s Not All About Numbers #3. Decision Trees:...
Boosting Your Method to SuccessImagine running a relay race. Each runner improves upon the previous one’s performance, and together, they win the race. That’s how these algorithms work — every latest model compensates for...
Artificial Intelligence
Exploring Gradient Boosting vs Linear Regression: Selecting the Best Prediction Tool and Developing a Streamlit App Creating your project’s environment Using VSCode for data evaluation Data Treatment Data...
Hey there! I’m Ana, a knowledge enthusiast and a machine learning apprentice. Welcome to my first post on Medium, where I’ll be sharing my journey and insights into the exciting world of knowledge evaluation...
Artificial Intelligence
Deep Dive into Softmax Regression Background: Multi-Class Classification Problems The Softmax Regression Model Cross-Entropy Loss Gradient Descent Practice Query Softmax Regression in Scikit-Learn Summary
With these gradients, we will use (stochastic) gradient descent to reduce the loss function on the given training set.You might be given a set of images and you must classify them into dogs/cats and...
Artificial Intelligence
Mastering Logistic Regression Background: Binary Classification Problems The Logistic Regression Model Log Loss Gradient Descent Implementation in Python The LogisticRegression Class in Scikit-Learn Summary
The next plot shows the log loss when y = 1:The log loss equals to 0 only in case of an ideal prediction (p = 1 and y = 1, or p = 0...
Artificial Intelligence
The Matrix Algebra of Linear Regression
Looking under the hood on the matrix operations behind linear regression11 min read·12 hours agoFitted ValuesWe've got now used some linear algebra to seek out the best-fitting parameters for a straightforward linear regression model....
Artificial Intelligence
A Comprehensive Overview of Regression Evaluation Metrics
Principally, all metrics exploded in size, which is intuitively consistent. That will not be the case for sMAPE, which stayed the identical between each cases.I highly encourage you to mess around with such toy...
Artificial Intelligence
Linear Regression In Depth (Part 2) Multiple Linear Regression Definition Closed-Form Solution Multiple Linear Regression Example Linear Regression in Scikit-Learn Analyzing the Regression Errors Gradient Descent The SGDRegressor Class Key Takeaways
Deep Dive into Multiple Linear Regression with Examples in PythonLet’s reduce the training rate from 0.01 to 0.001 by changing the parameter eta0 of the SGDRegressor:pipeline.set_params(reg__eta0=0.001)Let’s refit the pipeline to the training set and...
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