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Daily Insights from Magic Internet Math courses. Learn at https://mathacademy-cyan.vercel.app
๐Ÿ’ก Proposition I.41 If a parallelogram have the same base with a triangle and be in the same parallels, the parallelogram is double of the triangle. From: Euclid's Elements Learn more: Explore all courses:
๐Ÿ“– Logistic Function $p(X) = \\frac{e^{\\beta_0 + \\beta_1 X}}{1 + e^{\\beta_0 + \\beta_1 X}}$ models the probability that $Y = 1$ given $X$, ensuring $0 \\leq p(X) \\leq 1$. From: Intro to Statistical Learning Learn more: Explore all courses:
๐Ÿ“ Polynomial Uniqueness A polynomial of degree $t-1$ is uniquely determined by $t$ points. Conversely, $t-1$ points leave infinitely many degree $t-1$ polynomials consistent. From: frost Learn more: Explore all courses:
๐Ÿ“– Definition IV.3 A rectilineal figure is said to be inscribed in a circle when each angle of the inscribed figure lies on the circumference of the circle. From: Euclid's Elements Learn more: Explore all courses:
๐Ÿ“– Bayes Error Rate The Bayes error rate is $1 - E[\\max_j \\Pr(Y = j | X)]$, the lowest possible test error rate for a given problem. It is analogous to the irreducible error. From: Intro to Statistical Learning Learn more: Explore all courses:
๐Ÿ“ Radius of Convergence Every power series has a radius $R \\in [0, \\infty]$ such that it converges absolutely for $|x-a| < R$ and diverges for $|x-a| > R$. From: Real Analysis Learn more: Explore all courses:
๐Ÿ“– Support Vector Classifier (Soft Margin) Allows some observations to be on wrong side of margin or hyperplane, controlled by tuning parameter $C$. Larger $C$ = wider margin, more violations allowed. From: Intro to Statistical Learning Learn more: Explore all courses:
๐Ÿ“ Chinese Remainder Theorem If $\\gcd(m, n) = 1$, the system $x \\equiv a \\pmod{m}$, $x \\equiv b \\pmod{n}$ has a unique solution modulo $mn$. Proof: Since $\\gcd(m,n) = 1$, write $mk + nt = 1$. Then $c = bmk + ant$ satisfies both congruences. Uniqueness: if $c, d$ both work, then $mn \\mid (c - d)$. From: intro-discrete Learn more: Explore all courses:
๐Ÿ“– Sensitivity and Specificity Sensitivity = $\\frac{\\text{TP}}{\\text{TP} + \\text{FN}}$ (true positive rate). Specificity = $\\frac{\\text{TN}}{\\text{TN} + \\text{FP}}$ (true negative rate). From: Intro to Statistical Learning Learn more: Explore all courses:
๐Ÿ’ก Proposition V.2 If a first magnitude be the same multiple of a second that a third is of a fourth, and a fifth also be the same multiple of the second that a sixth is of the fourth, the sum of the first and fifth will also be the same multiple of the second that the sum of the third and sixth is of the fourth. From: Euclid's Elements Learn more: Explore all courses:
๐Ÿ“– Uniform Continuity $f$ is uniformly continuous on $S$ if $\\forall \\varepsilon > 0, \\exists \\delta > 0: |x-y| < \\delta \\Rightarrow |f(x) - f(y)| < \\varepsilon$ for all $x, y \\in S$. From: Real Analysis Learn more: Explore all courses:
๐Ÿ’ก Proposition I.28 If a straight line falling on two straight lines make the exterior angle equal to the interior and opposite angle on the same side, or the interior angles on the same side equal to two right angles, the straight lines will be parallel to one another. From: Euclid's Elements Learn more: Explore all courses:
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