Loading a Model

Load Data & Model

Assume you have trained a model and stored it under demonstration_model. We can now load the model and use it to make predictions using left and right DataFrames. In the first step, both the model and the data are loaded into memory.

import pandas as pd

from neer_match_utilities.model import Model
from neer_match_utilities.prepare import Prepare, similarity_map_to_dict
from pathlib import Path
from neer_match_utilities.custom_similarities import CustomSimilarities

# Load files

left = pd.read_csv('left.csv')
right = pd.read_csv('right.csv')

# Load custom similarity functions

CustomSimilarities()

# Load model

loaded_model = Model.load(
    'demonstration_model'
)

Harmonize Format

Next, we must ensure that the formatting logic remains consistent with that applied before training. Note that it is not necessary to redefine the similarity map, as it was stored and is loaded along with the model.

prepare = Prepare(
    similarity_map=similarity_map_to_dict(
        loaded_model.similarity_map
    ), 
    df_left=left, 
    df_right=right, 
    id_left='company_id', 
    id_right='company_id'
)

left, right = prepare.format(
    fill_numeric_na=False,
    to_numeric=['found_year'],
    fill_string_na=True, 
    capitalize=True
)

Make Suggestions

Now we can make suggestions:

# Make suggestions for the first observation in left

suggestions = loaded_model.suggest(
    left[:2], 
    right, 
    count=10, 
    verbose=0
)

suggestions

	left	right	prediction
0	0	0	0.458794
1	0	263	0.031737
2	0	530	0.007070
3	0	336	0.001577
4	0	602	0.001301
5	0	381	0.001137
6	0	436	0.001031
7	0	169	0.000992
8	0	517	0.000974
9	0	633	0.000819
10	1	1	0.999379
11	1	169	0.997775
12	1	245	0.949566
13	1	506	0.620147
14	1	279	0.372858
15	1	244	0.089429
16	1	207	0.046766
17	1	338	0.034049
18	1	607	0.027497
19	1	223	0.019611

Based on this output, we can assess whether the suggestion is correct.

left.iloc[1]

company_id                                                    810c9c3435
company_name             DEUTSCH-OESTERREICHISCHE MANNESMANNRÖHREN-WERKE
city                                                              BERLIN
industry                            BERGWERKE, HÜTTEN- UND SALINENWESEN.
purpose                BETRIEB DER MANNESMANNRÖHREN-WALZWERKE IN REMS...
bs_text                GENERALDIREKTION D SSELDORF MOBILIAR U UTENSIL...
found_year                                                        1890.0
found_date_modified                                           1890-07-16
Name: 1, dtype: object

right.iloc[1]

company_id                                                    8bf51ba8a0
company_name            DEUTSCH-OESTERREICHISCHE MANNESMANNRÖHREN-WERKE.
city                                                              BERLIN
industry                            BERGWERKE, HÜTTEN- UND SALINENWESEN.
purpose                BETRIEB DER MANNESMANNRÖHREN-WALZWERKE IN REMS...
bs_text                GENERALDIREKTION GRUNDST CKSKONTO M MOBILIEN U...
found_year                                                        1890.0
found_date_modified                                           1890-07-16
Name: 1, dtype: object