Translation of "n fact" to Japanese language:
Examples (External sources, not reviewed)
| In fact, it's guaranteed that eventually i will surpass n. | 数学的な証明については任せますが 今は私の言葉を信じてください |
| In fact, in general, if you have N entries, there are 2 to the power of N possibilities. | 2のN乗の可能性があるのです 従って思ったよりも多くの出力があるのです |
| The ln n in fact, any base log n is Big Theta of any other base log n as long as it's a constant. | 底が定数であるならΘ(log n)です 私はコンピュータ科学者なので 底が2の対数で考えることが多いですね |
| Is it n, n 1 over n, n over n 1, n divided by n 1, n 1 divided by n, or is it n squared 1 over n 1? | それとも n² 1 1でしょうか ここでnは標本集合におけるデータ点の 個数であることに注意してください |
| N. Down here. In fact because one half N. Squared has a smaller leading constant it's actually a smaller function. | より小さい関数に実際になっている そしてこれは この交点の所 だいたい90あたりまで真だ |
| Θ(n²), O(n²), and O(n³). | ビッグ オー記法は上界なのでO(n²)が有効です |
| Okay. So basically (log n)⁷ beats 9n(log n)² and n² ³ beats (log n)⁷ and 9n(log n)² beats n² ³. | 9n(log n)²はn² ³より優位なので |
| Now, if K is n 2 that's n times n 2 where n². | n 2のn倍はnの2乗 Θ(n²)になります |
| So I subscript n by n is the n by n identity matrix. | n掛けるnの単位行列 というのは おのおのの次元nごとに |
| So altogether we're talking about n n² or n³. | ダイクストラ法をより密度の高いグラフに適用した時の n³ log nよりよい値です |
| n times n minus one times n minus two. | 何回行ったのかを把握する変数だけでなく |
| If we divide through by n, we get 2 n n and divided by n is actually n. | すると2 nです |
| Russian(n, n) for lots of different values of n. | しかし結果は期待外れでした |
| n | n |
| N | 北 |
| N | 北緯South, the direction |
| N | N |
| N | Nunit description in lists |
| N | Nunit description in lists |
| N | N |
| ? N? ? | 哲希のチャランポラン どーにかなんねえかな |
| Log n is piddly as n gets big compared to n, and n is actually pretty piddly as n gets big compared to n². | nの成長率はn²よりも低くなります 重大な要素はn²だけです |
| Keep shoot 'n. Keep shoot 'n. | (機関砲の発射音) |
| Here we have n n 1. | nが全体数の時whileループを抜けるごとに 1ステップ分ステップダウンします |
| In fact, it takes at least n 1 edges to connect any graph within nodes. | 問題はBをツリーにできるかです |
| Could there be n 1 ways, n 1 squared, n 1 factorial, or 2 n 1? | どれが正しいか答えてください |
| So, it's really n times n plus m which is (n² nm). | このデータでいくとノードは6000の登場人物なので |
| We're much better with n log n. | 非常に長いリストの場合はソートがいいでしょう |
| With the very long list that were wanting to tap values of, you might as well just sort the whole thing. n, well what happens with n? n where look we're comparing n log n to n( n) which is n³ ². n³ ² is asymptotically larger than n log n so we're still better off just sorting the whole list. | nの平方根の場合はどうでしょう この場合はn log nを nのn倍 つまりnの3 2乗と比較します この値は漸近的にn log nより大きいので |
| Is the depth that we get this way log n, n, or 2 n, and are the number of leaves at the bottom log n, n, or 2 n? | リーフの数はlog n n 2ⁿのどれでしょうか |
| Adding up these three parts we get 2 n n(n 1) 2. | 試しにやってみましょう |
| Ctrl N | Ctrl N |
| N Go | N メッセージ 次のメッセージ |
| PAL N | PAL N |
| N no. | いやだ |
| Stop! n | 戻りなさい |
| And... n? | あとさあ 哲希 ん |
| Uu n... | う ん... |
| N o! | だ め |
| F(n) is in O(g(n)) there's our friend O that's really like saying f(n) g(n). | g(n)と同じか小さいでしょう |
| n here has to match this n here. | 言い換えると この行列の |
| It's n times the factorial of n 1. | この部分は再帰的関数の呼び出しです |
| So it's Θ(n²). It's order of n², as well as order of n³. | (log n)7は9n(log n)²より優位 n² ³は(log n)7より優位 |
| Or hear f(n) is some basic function, like for example n log n. | 私はビッグオー記法が本当は何を意味するか について考えるための いくつかの考え方を提示するつもりだ |
| But imagine if it was, you know, an n by n by n cube. | 任意の乗数で使用できます |
Related searches : Fill N - N Deposition - N Place - N Contrast - N Case - N Site - N Balance - N Principle - N Progress - N Hold - N Gauge - N Value - Based N
