Mike Chapman

I'm Giving It Up this September for pancreatic cancer research. rememberseptember.org.au/s/9905/11021/t Ok, so another fundraiser, this time for @PanKind_APCF I selected a smaller target of $500.00 I hope most of you aren't suffering from fundraising fatigue. I intend to cycle 68km.

@JoachimSchork Can you provide a sample data set. Please?

When using Polynomial Regression, choosing the right degree for the polynomial is crucial for balancing model complexity and performance. A polynomial that is too simple might miss important trends in the data, while one that is too complex can lead to overfitting. Here’s how to navigate this decision: ✔️ Start simple: Begin with a low degree (e.g., degree 2 or 3) and gradually increase, observing the model's performance on both training and validation data. ✔️ Cross-validation: Use k-fold cross-validation to assess how different polynomial degrees perform on unseen data. This helps reduce the risk of overfitting and ensures more generalizable results. ✔️ Look at residuals: Examine the residual plots. If the residuals show a clear pattern, you might need a higher degree polynomial. If they are randomly distributed around zero, your model is likely well-fitted. ✔️ Check for overfitting: If the training error is very low but the validation error is high, the model is likely overfitting, which can happen with a high-degree polynomial. When choosing the degree of your polynomial: ❌ Too low: A polynomial that is too low might miss important patterns in the data (underfitting). ❌ Too high: A polynomial that is too high can lead to overfitting, capturing noise in the data rather than the true underlying trend. ❌ Interpretability: Higher-degree polynomials make the model more complex and harder to interpret, especially for non-experts. How to implement in practice: 🔹 In R: Use poly() to fit polynomial terms in your model. Functions like cv.glm() (from the boot package) can be used for cross-validation to evaluate different polynomial degrees. 🔹 In Python: Use PolynomialFeatures from sklearn.preprocessing to create polynomial terms, and use GridSearchCV from sklearn.model_selection to optimize the degree through cross-validation. The graph demonstrates the impact of choosing different polynomial degrees in regression. Degree 1 (pink, dotted) underfits the data by failing to capture the true trend, while Degree 2 (blue, solid) provides the best fit to the quadratic nature of the data. In contrast, Degree 7 (orange, dashed) overfits by capturing noise, resulting in a complex and less generalizable model. Want to learn more? My Statistical Methods in R course covers topics like polynomial regression in more detail! Take a look here for more details: statisticsglobe.com/online-course-… #DataScientist #datasciencetraining #VisualAnalytics #pythonlearning #DataViz #Python #datastructure

@WeHaveWaysPod model meet Wed 11th Feb. All welcome to chat all things WW2, model making and general craic. Beginners encouraged to pop along and ask the hive mind questions. Registration link in the thread below . I'll see you on the Beach.

@bolderston_mark Interesting colour - love a triumph.

Triumph 2000 Your Thoughts Please and Thanks Again

What an incredible tribute from South Aussie farmer Harrison Schuster. Happy Australia Day everyone!

Well said Sir Rod Stewart.

@bolderston_mark Can’t beat the styling. Except for. Xk120. Colour is very cool.i hope the headlights a safety requirement.

Jaguar 3.8 Your Thoughts on this Please and Thanks Again Appreciated

@bolderston_mark Love them in all the variations

Triumph Stag Your Thoughts Please and Thanks Again

@bolderston_mark Hmmm … I don’t think so. Just a bit weird.

Alfa Romeo Fulvia Zagato Your Thoughts Please and Thanks

@bolderston_mark Just a bit silly, went a bit wrong somewhere.

Renault 16 Your Thoughts Please and Thanks Again

@Saganismm Just brilliant.

Carl Sagan explains the fourth dimension with rare simplicity

@RedFiveModels @Hush_Kit Not as glamorous as a Short Sunderland.

@Hush_Kit Now THAT fucker looks like a hushkit Ai special 🤣

Flying boat interception!

Not sure they should have done this - not really a classic shape.just doesn’t flow.

@bolderston_mark Oh yeah baby.

Jaguar E-Type Your Thoughts Please and Thanks Again

@bolderston_mark Where can I get one?

Ford Capri 3000E Your Thoughts Please

I want to like it, it’s amazing. Unfortunately it’s light pollution.

It ‘s common that many people will and do vote for what ever is not in their self-interest.

Geology destroys religion.........

@Peter_Fitz Too many.

Strong

@consequence I gave up May three years ago. I was told the next alcoholic might be my last ever. Sometimes I miss it mostly not. Difficult to replace in some social situations.

Sir Anthony Hopkins is celebrating 50 years of sobriety today

@AdamWatkinson1 I think it’s good to develop skills using other scales and kit themes.