作者查詢 / goldflower
作者 goldflower 在 PTT [ Python ] 看板的留言(推文), 共273則
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21F推: 單刀直入XDDDDD 阿不就只是 A: 欸 問你喔(一串code)04/18 02:46
22F→: A: 哪裡有bug啊? 這單刀直入真幽默04/18 02:47
46F推: 在so會被減分到爆吧XD04/18 16:31
47F→: so都要補自己試了哪些方法 產出哪些結果 想法等等04/18 16:32
48F→: 沒試到走投無路還真不敢問04/18 16:32
13F推: mac pyenv無敵論04/17 20:54
1F推: pd.read_csv(..., sep=' ', ...)04/07 22:22
4F推: 那可能是用tab分的吧 sep='\t' 看看04/07 23:27
5F→: 還不行你就傳個前幾行的版本上來看看04/07 23:28
7F推: 你把(n,m)和(m,1)做dot就是(n,1) (n,)就網址那種吧04/07 20:35
8F→: 不過想借標題問一下 我其實不太清楚(n,)這種表示法04/07 20:36
9F→: 好處在哪裡 除了可以直接內積得scalar以外04/07 20:36
10F→: 不然我一般使用都轉成2d array對我來說運算比較直覺04/07 20:37
11F→: 而且要內積直接np.sum(np.multiply(...))也可以04/07 20:38
12F→: 不曉得(n,)到底有啥優勢@@04/07 20:38
17F推: 寫數學時不會特別把nx1當作二維吧(雖然numpy上是如此)04/07 21:23
18F→: 不過可能就我自己很少不搭配矩陣用所以比較鑽牛角尖04/07 21:23
19F→: P大講的的確我會flatten完後做類似操作04/07 21:24
20F→: 感覺上是在純向量運算上這種表示法code會比較乾淨04/07 21:25
21F推: 想了下覺得純向量下nx1和1xn似乎都不太好04/07 21:27
22F→: 畢竟這些是在定義矩陣運算後才會出現的結果04/07 21:27
23F→: 突然覺得這種表示法其實比較嚴謹了哈哈 感謝二位04/07 21:28
1F推: 你可以畫個圖說明一下想要的效果XD 看字沒感覺04/02 20:34
1F推: https://i.imgur.com/48CQ7E7.png 這樣應該可切03/31 20:37
2F→: .load()不會讀全部檔案 有點像(但不是)cursor吧03/31 20:38
3F→: 我後面reshape那邊在耍白痴... 反正就中間for在切03/31 20:39
7F推: .load()是根據給的i,j去讀pixel 不會全抓03/31 20:51
8F→: 不過我只有試切一張幾百MB的tif而已@@03/31 20:51
10F推: 好奇所以後來行不行R?04/02 13:44
8F推: 應該就你training data沒做labelencoder吧?03/29 01:25
9F→: 記得scikit-learn的tree只吃數值 而且也只處理數值03/29 01:26
10F→: 所以你做完labelencoder後他會把你的categorical看成03/29 01:26
11F→: 數字 這應該不是你要的 所以就如gigayaya說的做OHE03/29 01:27
12F推: 像no_employees可以轉 因為有順序上的關係03/29 01:32
13F→: 但像country就要用one-hot 因為彼此間沒大小關係03/29 01:32
14F推: github.com/scikit-learn/scikit-learn/pull/489903/29 01:36
15F→: 可以看下這邊 反正結論就是目前沒這功能的樣子03/29 01:38
1F推: 你是不是apply的時候忘記把空白鍵拿掉R03/27 17:18
1F推: 後面加.dt.date03/27 17:02
1F推: 這好有趣XD 推個03/26 22:43