Pandas ValueError:matmul:输入操作数1的核心维度0不匹配。从不一致消息获取预测数据时
当我执行以下代码时,我得到了错误: ValueError:matmul:输入操作数1的核心维度0与gufunc签名(n?,k),(k,m?)->(n?,m?)不匹配(大小21459不同于1) 不和谐代码:Pandas ValueError:matmul:输入操作数1的核心维度0不匹配。从不一致消息获取预测数据时,pandas,numpy,scikit-learn,discord.py,Pandas,Numpy,Scikit Learn,Discord.py,当我执行以下代码时,我得到了错误: ValueError:matmul:输入操作数1的核心维度0与gufunc签名(n?,k),(k,m?)->(n?,m?)不匹配(大小21459不同于1) 不和谐代码: import discord import joblib from sklearn.preprocessing import OrdinalEncoder import numpy as np intents = discord.Intents().all() client = discord
import discord
import joblib
from sklearn.preprocessing import OrdinalEncoder
import numpy as np
intents = discord.Intents().all()
client = discord.Client(intents=intents)
loaded_model = joblib.load("finalized_model.sav")
@client.event
async def on_ready():
print("im ready")
@client.event
async def on_message(message):
enc1 = OrdinalEncoder()
text = message.content
array = np.array(text)
array = array.reshape(1, -1)
enc1.fit(array)
await message.channel.send(loaded_model.predict(enc1.transform(array)))
client.run("the bot token")
保存已训练模型的程序:
from sklearn.linear_model import LinearRegression
import pandas as pd
from joblib import parallel_backend
from sklearn.preprocessing import OrdinalEncoder
import joblib
import numpy as np
with parallel_backend('threading', n_jobs=1):
enc1 = OrdinalEncoder()
enc2 = OrdinalEncoder()
firstLine = True
model = LinearRegression()
df = pd.read_csv("Emotion_final.csv")
X = np.array(df["Text"]).reshape(1, -1)
y = np.array(df["Emotion"]).reshape(1, -1)
enc1.fit(X)
enc2.fit(y)
model.fit(enc1.transform(X), enc2.transform(y))
filename = 'finalized_model.sav'
joblib.dump(model, filename)