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JMP 函數（神經網絡）

大家好，

 

我使用神經網絡函數從 JMP 導出了 python 代碼。 我正在嘗試在 Spyder 上運行代碼，但有一個名為“jmp.mz”的函數，我不知道如何替換它。 我不知道這個功能是做什麼的。

 

誰能幫我這個？ 預先感謝您的寶貴時間。

 

祝你今天過得愉快。

 

艾莉森

高級統計建模基礎數據分析與建模回复：JMP 功能（神經網絡）

我不確定你做了什麼。 我以大班為例。 我建模了：重量和：年齡, ：性別， 和：高度作為輸入。 我將模型發佈到 Formula Depot。 我生成了Python代碼。 這裡是：

 

from __future__ import division
import jmp_score as jmp
from math import *
import numpy as np

""" ====================================================================
 Copyright (C) 2022-2023 JMP Statistical Discovery LLC. All rights reserved.
 
 Notice: The following permissions are granted provided that the above
 copyright and this notice appear in the score code and any related
 documentation. Permission to copy, modify and distribute the score
 code generated using JMP (r) software is limited to customers of JMP
 Statistical Discovery LLC ("JMP") and successive third parties, all
 without any warranty, express or implied, or any other obligation by
 JMP. JMP and all other JMP Statistical Discovery LLC product and
 service names are registered trademarks or trademarks of JMP
 Statistical Discovery LLC in the USA and other countries. Except as
 contained in this notice, the name of JMP shall not be used in the
 advertising or promotion of products or services without prior
 written authorization from JMP Statistical Discovery LLC.
 ==================================================================== """

""" Python code generated by JMP 17.2.0 """

def getModelMetadata():
 return {"creator": u"Neural", "modelName": u"", "predicted": u"weight", "table": u"Big Class", "version": u"17.2.0", "timestamp": u"2023-06-22T15:05:18Z"}

def getInputMetadata():
    return {
        u"age": "float",
        u"height": "float",
        u"sex": "str"
 }

def getOutputMetadata():
    return {
        u"Predicted weight": "float"
 }

def score(indata, outdata):

    sex_asCode = jmp.match(indata[u"sex"],{u"F":0,u"M":1}, np.nan)

    H1_1 = tanh((12.9380978259799 + -0.216077718694819 * indata[u"height"] + 0.5 * jmp.match(indata[u"age"],{12:-0.0752869145775503,13:1.43808466048513,14:2.51676030243735,15:1.74966392837427,16:-3.99748804536747,17:-1.63173393135173}, np.nan) + 0.5 * jmp.match(sex_asCode,{0:-1.0888433588967,1:1.0888433588967}, np.nan)))

    H1_2 = tanh((19.7761183161641 + -0.331952318291445 * indata[u"height"] + 0.5 * jmp.match(indata[u"age"],{12:-0.476738410666868,13:-2.86567218066002,14:0.848951695382413,15:1.24849250460232,16:6.92106266494234,17:-5.67609627360018}, np.nan) + 0.5 * jmp.match(sex_asCode,{0:1.56127362393991,1:-1.56127362393991}, np.nan)))

    H1_3 = tanh((1.43246192499634 + -0.037575857404148 * indata[u"height"] + 0.5 * jmp.match(indata[u"age"],{12:-0.519079596013513,13:-2.26923722344442,14:3.65113577518731,15:2.78561481785367,16:1.59523547291602,17:-5.24366924649907}, np.nan) + 0.5 * jmp.match(sex_asCode,{0:-0.207032194138191,1:0.207032194138191}, np.nan)))

    outdata[u"Predicted weight"] = 100.343111337815 + -28.0586522707582 * H1_1 + -16.1719623964746 * H1_2 + 2.89859037837539 * H1_3

    return outdata[u"Predicted weight"]

我沒有看到你問的功能。

回复：JMP 功能（神經網絡）

mz() 函數在 jmp_score.py 中定義，該函數在評分代碼的第一行中導入。

 

import jmp_score as jmp

 

您可以在以下位置找到 jmp_score.py：

蘋果
/庫/應用程序支持/JMP/17/scoring/Python

 

視窗

C:\Program Files\SAS\JMPPRO\17\Scoring\Python