Blackpill Mathematically proving facepill > heightpill

[nxm]

Proving facepill>heightpill

T=αF+(1-α)[η,λ,ε].[H,L,W]

α=f(F)≠k*F

To keep it simple I'll aprox with α=-kF+c

If the face is a 10, you don't mind about face (as it's non linear I guess there's a non zero weight at 10, I'll say a 30%), so a 3 in body would be around a 5 overall.

If face is a 1 you really mind about it so let go 90% so even a 10 in body wouldn't put a 1 face over a 2 overall

In that case k = 0.066, c= 0.966 so α=0.966-0.066*F

I prefer shorties, so η should be non linear, with a maximum on H optimal. I purpose the following term.

η(10-(H-1.Ho)²)

ε would be negative for my preference, but YMMV

There's another discussion with λ as some people would value length at different heights differently, here I purpose a 9/4 cycle negative sin function to start, but that would keep the peaks all the same weight.

λ(h)=-Λsin(9π/2Hh)

Nose, belly and feet shouldn't be huge, the other two add up but you might need a different freq sin to adjust the weight on those two, I'll leave it out for simplicity.

T=cF-kF²+(1-c+kF).((10-(H-1.Ho)²)+(int(Λ*sin(9π/2H h)*L(h) dh, 0,H))-εW).

Choose c, k, η, Ho, Λ, ε for your preference, maybe a different λ(h), and fill with F, H, L(h) and W of the subject to find the total points.

I don't agree with the strictly negative derivative of α(F), I think a 9 or 10 in F does make the α higher than at 6, although maybe not as high as a 1 or 2. Maybe something along the lines of

α(F) = e-p*F + q*F²

So α(0)=1 but α(10)>α(6).

I wouldn't go for a 0.75 constant α.

 

[Violet loner]

I don't understand it, but i'm agree with you

 

[Manlet_cel]

I don't understand it, but i'm agree with you

 

[Kooky Koala Kid]

There's another discussion with λ as some people would value length at different heights differently, here I purpose a 9/4 cycle negative sin function to start, but that would keep the peaks all the same weight.

So I do understand the concept of mu being used here for a length but you're very vague about the length

I don't agree with the strictly negative derivative of α(F), I think a 9 or 10 in F does make the α higher than at 6, although maybe not as high as a 1 or 2. Maybe something along the lines of

and by noting a "negative derivate" you are noting some sort of negtative relation, if you could please elaborate on what is negatively related to what

T=αF+(1-α)[η,λ,ε].[H,L,W]

Im also having a hard time understanding why you used two sets of vector coordinates and why you felt the need to use 3 dimensional vector doordinates

In that case k = 0.066, c= 0.966 so α=0.966-0.066*F

im also a bit of an IQcel so is this a rouge estimate of the constant c or is that the pure raw value

I prefer shorties, so η should be non linear, with a maximum on H optimal. I purpose the following term.

if its non linear is it exponential or is it more logarithmic growth, I can denounce any chance of a quadratic cubic or quartic function because in nature it is basically useless, just a question again, im a little bit of an IQcel

T=cF-kF²+(1-c+kF).((10-(H-1.Ho)²)+(int(Λ*sin(9π/2H h)*L(h) dh, 0,H))-εW).

with H being substituted in a radians pi function, at 9/2 being >2 what if H = 1, surpassing 2 pi in terms of radians just means back to the beginning in the base unit circle, is that a negligible outcome or what??


again these are all my questions and observations im severely retardsed and deformed with a 60iq most likely, please answer these queestions if you can!

 

[AtrociousCitizen]

I see.

 

[Hoor Al-Ayn]

T=αF+(1-α)[η,λ,ε].[H,L,W]

.is users will believe this is legit

 

[autistic.goblin]

Rice ramblings

 

[InvoluntaryChigga]

Over for quantcels

 

[Kooky Koala Kid]

.is users will believe this is legit

JFL I was confused as hell when i saw that

 

[Kooky Koala Kid]

Over for quantcels

if sin is in quant then dumb chads and fucking foids would never be able to get their finger in the door for jobs like that

 

[Kooky Koala Kid]

I see.

I dont

 

[Hoor Al-Ayn]

JFL I was confused as hell when i saw that

he doesn't even define any of the variables. there's a lot of funny things here, like the fact he puts a dot multiplication for a three dimensional vector for no reason.
its gibberish.

 

[T1Dcel]

he doesn't even define any of the variables. there's a lot of funny things here, like the fact he puts a dot multiplication for a three dimensional vector for no reason.
its gibberish.

"dot multiplication" gives me PTSD from further maths

 

[Kooky Koala Kid]

he doesn't even define any of the variables. there's a lot of funny things here, like the fact he puts a dot multiplication for a three dimensional vector for no reason.
its gibberish.

yeah from my observations the first thing I noticed was the three dimensional vector and then he started talking about linear comparisons then negative derivatives, It went from 3 dimensional to 2 dimensional immediately, I wanted to see if he could help me understand the gibbberish or where he was getting to with this "mathematical analysis" I still do believe the claim he's making is true but the math he's doing is so irrelevant, he even threw a lil bit of physics in there talking about wavelengths , again usually represented in a 2 dimensional data model

 

[Kooky Koala Kid]

yeah from my observations the first thing I noticed was the three dimensional vector and then he started talking about linear comparisons then negative derivatives, It went from 3 dimensional to 2 dimensional immediately, I wanted to see if he could help me understand the gibbberish or where he was getting to with this "mathematical analysis" I still do believe the claim he's making is true but the math he's doing is so irrelevant, he even threw a lil bit of physics in there talking about wavelengths , again usually represented in a 2 dimensional data model

to add on to this the "negative derivative" part was used so wrongly and didn't really bridge into an inverse relationship

 

[Hoor Al-Ayn]

yeah from my observations the first thing I noticed was the three dimensional vector and then he started talking about linear comparisons then negative derivatives, It went from 3 dimensional to 2 dimensional immediately, I wanted to see if he could help me understand the gibbberish or where he was getting to with this "mathematical analysis" I still do believe the claim he's making is true but the math he's doing is so irrelevant, he even threw a lil bit of physics in there talking about wavelengths , again usually represented in a 2 dimensional data model

lambda is both seemingly a function (since he inputted it as "λ(h) = Λsin(9π/2Hh)") and a variable here, there's no point in deciphering this nonsense lol, I doubt it has any connection with wavelength.
good job to OP for giving me a good laugh at least

 

[nxm]

So I do understand the concept of mu being used here for a length but you're very vague about the length

and by noting a "negative derivate" you are noting some sort of negtative relation, if you could please elaborate on what is negatively related to what

If F = 1 (ugly) then α is high meaning you care a lot about the face.
If F = 10 (very attractive) then α is lower, meaning you care less about the the face.

Im also having a hard time understanding why you used two sets of vector coordinates and why you felt the need to use 3 dimensional vector doordinates

it’s not truly a vector in the linear algebra sense, but it mimics the dot product structure the vector isn't used for directionality or spatial reasoning it's just notation. It could've been written out longform, but this format helps highlight that Each feature (height, length, weight) has its own importance weight (η, λ, ε) And you want to sum the influence of all three

im also a bit of an IQcel so is this a rouge estimate of the constant c or is that the pure raw value

this is a rough but grounded estimation from two data points, not a totally arbitrary constant.

Using two points (F=1, α=0.9) and (F=10, α=0.3), we can solve for k and c: Slope (k) = (0.3 - 0.9) / (10 - 1) = -0.066 Plug into α = -0.066F + c use F = 1 and α = 0.9 0.9 = -0.066(1) + c c ≈ 0.966

if its non linear is it exponential or is it more logarithmic growth, I can denounce any chance of a quadratic cubic or quartic function because in nature it is basically useless, just a question again, im a little bit of an IQcel

This is a quadratic function, not exponential or logarithmic. It’s shaped like a parabola and is centered at Ho, which is your ideal height. the use of a concave-down parabola is perfectly functional

with H being substituted in a radians pi function, at 9/2 being >2 what if H = 1, surpassing 2 pi in terms of radians just means back to the beginning in the base unit circle, is that a negligible outcome or what??

Not necessarily it just means the sine term will oscillate rapidly, and its average impact might reduce, unless modulated carefully by L(h).

again these are all my questions and observations im severely retardsed and deformed with a 60iq most likely, please answer these queestions if you can

 

[nxm]

tbh i just made this shit for the lols bruh, I'm bored at 4am and tried to see what I can cook, facepill > heightpill tho

 

[nxm]

but you some smartcells ngl @Hoor Al-Ayn @Kooky Koala Kid

 

[Hoor Al-Ayn]

but you some smartcells ngl @Hoor Al-Ayn @Kooky Koala Kid

thanks OP. this post is my kind of humor honestly, idk if that was the intention but its funny nonetheless.

tbh i just made this shit for the lols bruh, I'm bored at 4am and tried to see what I can cook, facepill > heightpill tho

I'm curious how much thought was put into this, do all the variables have meaning behind them?

 

[nxm]

thanks OP. this post is my kind of humor honestly, idk if that was the intention but its funny nonetheless.

yea it was for the lols

I'm curious how much thought was put into this, do all the variables have meaning behind them?

F is the face rating, usually on a scale from 1 to 10. It reflects how conventionally attractive someone’s face is.

H is height (e.g., H = 1.6 for 160 cm).

L(h) represents the body’s length profile at a given height h. This could refer to proportions like leg-to-torso ratio or other distribution-based body features.

W is weight. You can treat this as a general factor for body composition

α(F) is a key function that determines how much weight you give to the face when evaluating overall attraction. It's dynamic meaning how much you care about the face depends on how good the face is. α might be high when the face is a 1 (ugly, so it matters a lot), lower at 6, but not as low at 10 (very attractive, so you may care less because it's already ideal).

η(H) is your height preference function. a quadratic curve with a maximum at your optimal height (Ho). So η(H) = 10 − (H − Ho)² gives you a peak attractiveness at Ho and decreasing attractiveness as you move away from it.

λ(h) is a function that models how much you like certain body proportions at different heights. a sine wave (with adjustable amplitude Λ and frequency tied to height) to capture cyclic preferences, you might favor certain proportions at some parts of the body more than others. The use of a sine function here reflects repeating structure (like hips, waist, shoulders) that affects appeal differently along the vertical axis.
ε is the weight penalty factor. It controls how much weight (W) matters to you. If ε is positive, higher weight reduces the total score. If you personally prefer thinner individuals, ε would be a positive number.

k and c are constants used in the linear approximation of α(F) = −kF + c. control how quickly the importance of face drops off as facial rating improves.

Λ is the amplitude of the λ(h) sine function. It controls how strongly the body proportion preferences affect the total score.

Ho is your ideal or preferred height. It’s the value of H where η(H) hits its maximum (usually 10).

 

[InvoluntaryChigga]

if sin is in quant then dumb chads and fucking foids would never be able to get their finger in the door for jobs like that

You underestimate dei