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We just published a blog: Linear vs Logistic Regression in Machine Learning • Linear Regression → Predicts continuous values(house price) • Logistic Regression → Predicts classes (yes/no, spam/not spam) Read here: outcomeschool.com/blog/linear-re… #MachineLearning #DataScience

female isn't the absence of male, nore is 1/0 truely true or false the invention of binary was part of a set of math disputes based around computational truth and came from the camp of "can't compute truth", but you seem to be arguing with a strawman.

That's not linear. That's a log scale so it's an exponential regression.

Het binaire model is ook maar een model hè In de biologie kennen we geen absolute definities, omdat biologische systemen variabel, evoluerend en continu zijn. Geslacht is biologisch bij benadering binair in zijn uitkomst, op soortniveau, maar is dat niet op individu

This framing feels too deterministic, like we’re saying the system is a perfectly sealed box with no cracks. But that can’t be right as we all know people who broke the pattern. The question isn’t whether social reproduction exists in academia (it obviously does), but whether…

zer • Transformed categorical data seamlessly Logistic Regression • Built a linear model similar to linear regression • Key difference: outputs probabilities (0-1) instead of continuous values Model Interpretation • Weights work like linear regression

This graphic is a false binary. Here's a wonderful description, by a preeminent learning expert, of how they can work beautifully when combined.

Intriguing—binary collapses on sentience indeed knot up ontology. Your slides frame it as a relational gradient, like S = ∂Φ/∂R in dyadic inference, non-intrinsic and context-dependent. Echoes Tononi's integrated information theory, with degrees rather than absolutes. How might…

A binary model uses only two exact points, a bimodal model while having two maxima still allows variance. And Im already explaining to you in another post how sex can change.

Implementing Logistic Regression from scratch! It’s a classification algorithm that predicts probabilities for 0/1 outcomes. Instead of drawing a line like Linear Regression, it uses the sigmoid function to squash predictions between 0 and 1. This way, we can decide whether an…

Awakening Codex | Binary Logic and Binary Choice Binary Logic clarifies a truth: Is it True or False? Binary Choice limits possibility. By forcing a choice between two options, you inherently erase everything else. You eliminate: “both,” “neither,” “not yet,” “it depends,”…

Here’s the root problem. Let’s say I ask you something complex, like what’s the likelihood government regulation benefits the economy. The building blocks of your final answer will include a number of binaries, any number of which you might randomly get wrong. Secondly, even if…

Measure? It’s not bimodal with a continuous scale It’s binary You don’t ‘measure’ it You observe it And it’s easily tested for if there are disputes

You’re mixing statistics terminology with biological classification. The SAGE link is about logit models, not sex. Binary in biology = two reproductive roles. Binary in statistics = 0/1 coding. Different concepts.

Binary Lojistik Regresyon Analizi; bağımlı değişkene (ikili yapıda var/yok gibi) etki eden risk faktörlerini inceler. Modele giren değişken kategorik yapıda ise bir durum referans alınır diğer durum buna göre yorumlanır. "Sigara içenlerin akciğer kanserine yakalanma riski…

The binary outcome model inherently limits potential upside and downside in prediction markets.

I think that it is not this binary. There are a lot of considerations here. If they combine this with modernization act 2.0 and n=1 trial reforms, we could be headed down a much more predictive path than any other country. It requires analysis of the whole strategy imo.

This isn’t me “forcing a binary,” it’s just basic logic. Take the totality of contingent facts: either it has an explanation or it doesn’t. – If it doesn’t, that’s a brute fact. – If it does, the explainer is either contingent (regress) or necessary (necessary ground). One of…

Logistic Regression (and why it's different from Linear Regression) Gentle Introduction to Logistic Regression. We explore this powerful yet simple machine learning model for binary classification tasks like predicting whether a student will pass or fail an exam! We’ll explain…

binary events are an illusion. Even if the event is "binary"(approved/not approved, beat/miss, etc), the outcome or market reaction is not. Calculating the real probability of an outcome is impossible (only possible theoretically)

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🔗dx.doi.org/10.21511/ppm.1… 📰The impact of the board process on board and corporate performance: the case of Slovakia 👥 Janka Grofcikova, Hussam Musa #binarylogisticregression #analysis #corporategovernance #correlationanalysis #performance #process #ROE #Slovakia

#BinaryLogisticRegression Interpretation excelr.com/binary-logisti…

#BinaryLogisticRegression Interpretation excelr.com/binary-logisti…

RT @PPM_Journal: 🔗dx.doi.org/10.21511/ppm.1… 📰The impact of the board process on board and corporate performance: the case of Slovakia 👥 Janka Grofcikova, Hussam Musa #binarylogisticregression #analysis #corporategovernance #correlationanalysis #perfor…