Translation of "似た p " to English language:
Examples (External sources, not reviewed)
| P P または | So chart state 0 includes the following parse states |
| p掛ける (p p)の1と p 2 pでp p (1 p)で 綺麗な式にまとまりました | And if you want to factor a p out of this, this is going to be equal to p times, if you take p divided p you get a 1, p square divided by p is p. |
| P Q P Q P Q Q P | And the sentences are P or not P, P and not P, |
| p 1 pで p ( 2p) 2p 2で p p 2 p 3です | And then this term over here, this whole thing over here, is going to be plus p times 1 is p. p times negative 2p is negative 2p squared. |
| P P | Let's say that this is our grammar |
| P P とPー です | Once again, based on this P, I'm going to start bringing in rules 1 and 2. |
| P. T. P | F, L, E, P, T, P L, E, P, F, L, F, L, E, P, T, P, L, F, E, T. |
| A P P | APPLE. |
| P(A) Ʃ P(A B) P(B) | Now in probability terms, people often write it as follows |
| P H R はP H R S P S | Let me just do this over here. |
| S P P P またPが何もなしと 書き換えられるPythonコードです | It's that grammar of balanced parentheses. |
| したがってコードは 3 p 1 p 1 p になります | So, to get all 3 of them together, we just multiply these by 3. |
| p 1はpです | So that cancels out. |
| 0 pは pです | So this is going to be equal to 1 minus p. |
| Pは P を得たあと2つ目のルールでPを消します | The first one looks pretty good. I just apply rule 1. |
| P P とあります | Another way to think about that is let's say that we're in a particular state like this one |
| P A B P B A P A P B となります P B A を尤度 ゆうど と言います | P of A given B where B is the evidence and A is the variable we care about is P of B given A times P of A over P of B. |
| P | P |
| p. | p. |
| P . | What's next? |
| P ... | P . |
| P ...? | P ... P ...? |
| P ...? | Teacup! |
| P | Similarly, over here I'm going to apply rule one three times. |
| P... | P... |
| P X3 X₁ P A X₁ P X3 X₁ A P A X₁ です これが全確率です | P of X3 given X1 is the sum of P of X3 given X1 and A times P of A given X1 plus the A complement, which is X3, conditional X1 and not A times P of not A given X1. |
| あんた J. P. | You're J. P. Prewitt. |
| あい行くぞE, F, L, E, P, T . P, L, E, P, F, L, E L, E, P, T, L, P, E, F, E, T, Z, E, T. | All right. E, F, L, E, P, T P, L, E, P, F, L, E L, E, P, T, L, P, E, F, E, T, Z, E, T... |
| 3つ目は x p x p x | Valid. |
| P Y P Y X P X P Y X P X となります これに数字を当てはめると0 6 0 2と | You can actually compute this using total probability where P(Y) equals P(Y_BAR_X) times P(X) plus P(Y_BAR_ X) times (P X). |
| ピンクの p を得るこの p プラス p 以上 1 プラス プラスです | Now let's add that pink p to both sides of this equation. |
| P Y S C R I P T E R | And right here, this environment is called PyScripter. |
| SをPに代入したのでPになります | Rule 0 and rule 1 both apply to S, so I'm going to yield 2 things. |
| p priority | p priority |
| Pブロック | p Block |
| Pブロック | p Block |
| P next? | Here, you can watch our brave bulls battle with their horns. |
| P. シャー... | OK. P. Sher... |
| シャー... P. | Sher... |
| Pシャーマン... | P. Sherman... |
| Pシャーマン | Awake. P. Sherman. |
| プラットフォームP. | Platform B. |
| P. S. | P.S. |
| それぞれの値から算出できます P H S R P S R P H S R P S R | P of happiness given S and R times P of S and R, which is of course the product of those 2 because they are independent, plus P of happiness given not S R, probability of not as R plus P of H given S and not R times the probability of P of S and not R plus the last case, |
| よって 分散はp (1 p)です | So p times 1 minus p, which is a pretty neat, clean formula. |
